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Munich School for Data Sciences (MUDS)

The aim of the Munich School for Data Science (MUDS) is to educate the next generation of Data Scientists at the interface of data science and four different application areas: Biomedicine, Plasma Physics, Earth Observation, and Robotics. The common ground in these different application areas is in the data-based and model-based research approaches. The training at MUDS is designed to explore new ways to connect these two poles.

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The MUDS educational program is a combination of introductory fundamentals of data science, as well as relevant interdisciplinary courses and active research training in each specific application area and educational track. In addition to the general training program, each doctoral researcher defines an individual study plan together with the supervisors. In this way, the training program is specifically tailored to the research profile and needs of the doctoral student.

The MUDS curriculum includes:

Basic and advanced scientific courses (e.g. Data Science Block Course)

Transferable skill courses

Bi-weekly seminar series

Annual summer schools

Participation in (international) conferences

Yearly checkpoint meetings with Thesis Advisory Committee (TAC)

As a member of the Helmholtz Information & Data Science Academy (HIDA), MUDS doctoral researchers have access to a series of attractive events, including hackathons, career days, symposia, and lectures. Moreover, they can complete research stays at a national and international level.

Research Network

At MUDS, Helmholtz Munich ( HMGU ), the German Aerospace Center ( DLR ) and the Max Planck Institute for Plasma Physics ( IPP ) have teamed up with the Technical University and the Ludwig Maximilian University in Munich to forge an internationally visible and highly attractive research network, with support from the Leibniz Computing Centre and the Max Planck Computing & Data Facility. To promote application-oriented doctoral projects in biomedicine, MUDS has established an industry track with collaborations with Roche Penzberg and Boehringer, and is actively reaching out to other industry partners to extend this track. 

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Funding and Duration of the Program

Doctoral researchers within MUDS are funded through PhD contracts (e.g. “E13” TVöD or TV-L, depending on the institution of employment) over a period of four years.

Learn more : https://www.mu-ds.de/

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As curious as we are? Discover more.

  • Our Research
  • People at Helmholtz

phd data science munich

Bavarian policymakers are interested in engaging in a wide variety of cooperative efforts that will help further develop artificial intelligence in Bavaria - among others with the Bavarian AI Council. The Munich School for Data Science (MUDS) has a decisive role to play in this. An interview with Fabian Theis, MUDS spokesperson, and Manfred Wolter from the Bavarian Ministry of Economics.

  

Hope for Diabetics

Diabetes is still incurable. But with the help of data science, this could soon change. At MUDS, Karin Hrovatin is researching the cells involved in insulin production. The goal is to stimulate hormone production again in the future.

Healing by Gene Therapy?

Deciphering the gene regulatory codes in our cells could improve the treatment of numerous diseases such as cancer or rheumatism in the future. MUDS doctoral researcher Laura Martens wants to contribute to this with her data science expertise.

phd data science munich
  • Courses for personal skills training and career development (transferable skills): access for all MUDS promoters to relevant courses offered at the partner sites; in addition, it is possible to attend tailor-made trainings organised by the MUDS office
  • MUDS certificate confirming participation in the programme   
  • "Research at MUDS is great: I can learn from people in other fields and get ideas that I can also apply to biology." Karin Hrovatin, researches with Data Science on Diabetes at MUDS

    Funding and Duration of the Programme

    The program extends over four years and offers continuous funding. The remuneration corresponds to the conditions for doctoral contracts of the respective partner institution and is based on the TVöD or TV-L.

    Application and Further Information

    There is a central recruitment round once or twice a year. The MUDS location and thus the location for all courses is Munich. The programme language is English. The programme starts every winter semester, the application phase takes place annually in autumn and every second year additionally in spring/early summer.

    Are you interested in advancing your research at a top location for computational science in Germany? Then apply at  MUDS

    phd data science munich

    Cosmin I. Bercea Doctoral Researcher MUDS

    Michael Bergmann

    Michael Bergmann Doctoral Researcher MUDS

    Frank Jenko, IPP

    Hans-Joachim Bungartz, TUM

    phd data science munich

    Jianxiang Feng Doctoral Researcher MUDS

    Rudolph Triebel, DLR

    Stephan Günnemann, TUM

    Robin Greif

    Robin Greif Doctoral Researcher MUDS

    Nils Thuerey, TUM

    Katharina Hechinger

    Katharina Hechinger Doctoral Researcher MUDS

    Göran Kauermann, LMU

    Xiaoxiang Zhu, DLR

    phd data science munich

    Christoph Koller Doctoral Researcher MUDS

    phd data science munich

    Benedikt Mairhörmann Doctoral Researcher MUDS

    Pascal Falter-Braun, HMGU / LMU

    Kurt Schmoller, HMGU

    phd data science munich

    Kislaya Ravi Doctoral Researcher MUDS

    phd data science munich

    Mara Stadler Doctoral Researcher MUDS

    Christian L. Müller, HMGU, LMU

    Till Bartke, HMGU

    Marco Stock

    Marco Stock Doctoral Researcher MUDS

    Antonio Scialdone, HMGU

    Maria Colomé-Tatché, HMGU

    Aysim Toker

    Aysim Toker Doctoral Researcher MUDS

    phd data science munich

    Victor Artigues Doctoral Researcher MUDS

    Tobias Blickhan

    Tobias Blickhan Doctoral Researcher MUDS

    Alejandra Castelblanco

    Alejandra Castelblanco Doctoral Researcher MUDS

    Anne Hilgendorff , LMU

    Sugandha Doda

    Sugandha Doda Doctoral Researcher MUDS

    Vladyslav Fediukov

    Vladyslav Fediukov Doctoral Researcher MUDS

    Johann Bals, DLR

    Constantin Gahr

    Constantin Gahr Doctoral Researcher MUDS

    Simon Geisler

    Simon Geisler Doctoral Researcher MUDS

    Xenofon Giannoulis

    Xenofon Giannoulis Doctoral Researcher MUDS

    Eleftheria Zeggini , HMGU

    Na Cai , HMGU

    Patrick Hanel

    Patrick Hanel Doctoral Researcher MUDS

    Celia Martinez-Jimenez, HMGU

    Henrik von Kleist

    Henrik von Kleist Doctoral Researcher MUDS

    Narges Ahmidi, HMGU

    Daniel Rückert, TUM

    Christopher Lance

    Christopher Lance Doctoral Researcher MUDS

    Daniel Kotlarz, LMU

    Svitlana Oleshko

    Svitlana Oleshko Doctoral Researcher MUDS

    Annalisa Marsico, HMGU

    Sergio Picart-Armada

    Boehringer Ingelheim

    Ghalia Rehawi

    Ghalia Rehawi Doctoral Researcher MUDS

    Patrick Schwehn

    Patrick Schwehn Doctoral Researcher MUDS

    Pascal Falter-Braun, HMGU

    Korbinian Schneeberger, LMU

    Oleg Vlasovets

    Oleg Vlasovets Doctoral Researcher MUDS

    Christian L. Müller, H.AI/LMU

    Annette Peters , HMGU

    Simon Wengert

    Simon Wengert Doctoral Researcher MUDS

    Na Cai, HMGU

    Matthias Heinig , HMGU

    Dominik Winkelbauer

    Dominik Winkelbauer Doctoral Researcher MUDS

    Yehor Yudin

    Yehor Yudin Doctoral Researcher MUDS

    Hans-Joachim Bungartz

    Frank Jenko

    David Coster

    Henning Zwirnmann

    Henning Zwirnmann Doctoral Researcher MUDS

    Suprevisors:

    Sami Haddadin, TUM

    More Schools

    phd data science munich

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    phd data science munich

    We do not use cookies on our website without your consent. Only after your consent do we process anonymous data, from which pseudonymized user profiles are created and evaluated. For this purpose we use the web analysis service software Matomo. Here you can activate or deactivate the cookie. You can change your settings at any time.  Our privacy policy.

    Graduate School for Data Science

    Munich school for data science founded.

    Munich School for Data Science @ Helmholtz, TUM & LMU (MuDS)

    Biomedicine, Plasmaphysics, Robotics: digitalised research delivers huge amounts of data. This data holds a great amount of potential - if it can be used effectively. To this purpose the newly founded Munich School for Data Science @ Helmholtz, TUM & LMU (MuDS) will train new researchers in this field. 

    The aim of the Graduate School is to make big data useable. That means, that huge amounts of data must be analysed and interpreted. Leading coordinator of the project is  Fabian Theis , Professor for Mathematical Models of Biological Systems at the TUM Department for Mathematics.

    "For great challenges, we need great solutions. For this project, we are bringing together important key-players from the greater Munich area and establishing a unique and strong resource for research and training, " says Theis, who is also the Director of the Institute for Computational Biology at the Helmholtz Zentrum München.

    Data Science - combining implementation and methodology 

    Why experts, who can evaluate such amounts of data are important, can be illustrated with a simple example: each cell in our bodies has the genetic material of roughly 3 billion base pairs - that is the equivalent of a library with 3000 books, each with 1000 pages on each of which 1000 letters are typed. In order to research individual cells, the help of intelligent algorithms is therefore essential. 

    Doctorate students of the Graduate School combine Data Science with other sciences such as bio-medicine, plasma physics, robotics and earth observation. The bilateral projects are each created by bringing together a domain-specific application partner and a methodical partner. The first announcement for applications for PhD positions at the Graduate School will be published in December 2018. 

    Since 2016, the TUM Department of Mathematics already offers the Masters course " Mathematics in Data Science ", which also concentrates on teaching mathematical processes and algorithms for analysing big data. 

    Munich School for Data Science - the Key-Players

    The founders of the Munich School for Data Science are the Helmholtz Zentrum München, the Max-Planck-Institute for Plasmaphysics (IPP), the German Aerospace Center (DLR), the Technical University of  Munich (TUM) and the Ludwig-Maximilians-Universität München (LMU). Two large computer centres are also involved, the Leibniz Supercomputing Centre (LRZ) and the Max Planck Computing & Data Facility (MPCDF).

    The Munich School for Data Science @ Helmholtz, TUM & LMU ( MuDS ) will be supported with a total of twelve million Euros over six years. Half of this sum comes from the participating institutions, the other half has been granted by the Helmholtz Association of German Research Centres.

    ESG Data Science

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    Data Science

    Interested in studying Data Science? -> Information event 22 January 2024

    Join our program MSc Data Science at Ludwig-Maximilians-Universität (LMU) Munich. LMU Munich is the first university in Germany that offers an elite graduate program in Data Science in English .

    Data Science is the science of extracting knowledge and information from data and requires competencies in both statistical and computer-based data analysis. The elite program Data Science is an interdisciplinary program and is carried out jointly by the Department of Statistics and the Institute for Informatics at LMU Munich. The program is part of and is supported by the Elite Network of Bavaria .

    The curriculum of the elite master program Data Science is a modularised study program . Students learn statistical and computational methods for collecting, managing, and analysing large and complex data sets and how to extract knowledge and information from these data sets. The program also comprises courses on data security, data confidentiality, and data ethics . In the practical modules students will tackle real-world problems in cooperation with industrial partners . Other highlights of the program are the summer schools and the focused tutorials.

    Upon graduation our students are well prepared for a career as a data scientist in the private or public sector in fields such as applied economics, political science, sociology, education, medicine, public policy, and media research. Students may also pursue a doctoral study in a variety of academic disciplines that require quantitative analysis.

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    LMU Munich offers a broad range of doctoral programs  as well as some umbrella structures. In addition, the university cooperates with other institutions on a doctoral level.

    For further information on the academic focus of a doctoral program as well as the application procedures and closing dates, please refer to the website of the specific program. If you have any questions on a specific program, please contact the coordinator / managing director of the respective program directly.

    As an alternative to participating in a doctoral program, LMU Munich offers graduates the option to complete individual doctoral studies in more than 100 subjects. Doctoral candidates are also supervised within the framework of research projects , academic institutions and research networks .

    Humanities and Cultural Studies

    • Cultures of Vigilance. Transformations – Spaces – Practices  (DFG: SFB 1369 - Integrated Research Training Group)
    • Doctoral Program Buddhist Studies
    • Doctoral Program Classical and Ancient Studies (PAW)
    • Doctoral Program Environment and Society
    • Doctoral Program Medieval and Renaissance Studies
    • Doctoral Program of Modern and Contemporary History (ProMoHist)
    • Family Matters. Figures of Allegiance and Release  (DFG: Research Training Group 2845)
    • Graduate School Language & Literature: Class of Culture and History. American History – History of the Americas
    • Graduate School Language & Literature: Class of Language
    • Graduate School Language & Literature: Class of Language Education
    • Graduate School Language & Literature: Class of Literature
    • International Doctoral Program "Transformations in European Societies"
    • Munich Graduate School for East and Southeast European Studies
    • Philology. Practices of Pre-modern Cultures, Global Perspectives and Future Concepts (Elite Network of Bavaria: International Doctoral Program)

    Social Sciences and Economics

    • Doctoral Training Program in the Learning Sciences (DTP)
    • Munich Graduate School of Economics (MGSE)

    Natural Sciences and Medicine

    • Advanced Medical Physics for Image-Guided Cancer Therapy (DFG: Research Training Group 2274)
    • Atherosclerosis – Mechanisms and Networks of Novel Therapeutic Targets (DFG: SFB 1123 - Integrated Research Training Group)
    • Cell-Fate Decisions in the Immune System (DFG: SFB 1054 - Integrated Research Training Group)
    • Chemical Biology of Epigenetic Modifications (DFG: SFB 1309 - Integrated Research Training Group)
    • Chromatin Dynamics (DFG: SFB 1064 - Integrated Research Training Group)
    • Doctoral Program Clinical Pharmacy
    • Doctoral Program "Infection Research on Human Pathogens@MvPI"
    • Emergence of Life: Exploring Mechanisms with Cross-Disciplinary Experiments (DFG: SFB Transregio 235 - Integrated Research Training Group)
    • Graduate School Life Science Munich: From Molecules to Systems
    • Graduate School of Quantitative Biosciences Munich
    • Graduate School of Systemic Neurosciences
    • i-Target: Immunotargeting of Cancer (Elite Network of Bavaria: International Doctoral Program)
    • Konrad Zuse School of Excellence in Reliable AI (relAI) (DAAD)
    • Nanoagents for Spatiotemporal Control of Molecular and Cellular Reactions (DFG: SFB 1032 - Integrated Research Training Group)
    • Perception in Context and its Neural Basis (DFG: Research Training Group 2175)
    • Ph.D. Program Medical Research in Epidemiology & Public Health
    • Ph.D. Program Medical Research in Genomic and Molecular Medicine – Personalized Approaches to Childhood Health
    • Ph.D. Program Medical Research – International Health  (DAAD: exceed)
    • Ph.D. Program Oral Sciences
    • Predictors and Outcomes in Primary Depression Care  (DFG: Research Training Group 2621)
    • Statistics: Theory and Methods of Empirical Modelling
    • Targets in Toxicology – Deciphering Therapeutic Targets in Lung Toxicology (DFG: Research Training Group 2338)
    • Trafficking of Immune Cells in Inflammation, Development and Disease (DFG: SFB 914 - Integrated Research Training Group)

    Umbrella Structures

    • Graduate School Language & Literature Munich (GS L&L)
    • Munich Graduate School of Sociology (MuGSS)
    • Munich Medical Research School (MMRS)

    International Max Planck Research Schools (IMPRS) in which LMU Munich participates

    • IMPRS Biological Intelligence
    • IMPRS for Molecular Life Sciences: From Biological Structures to Neural Circuits
    • IMPRS for Quantum Science and Technology
    • IMPRS for Translational Psychiatry
    • IMPRS on Advanced Photon Science
    • IMPRS on Astrophysics
    • IMPRS on Elementary Particle Physics

    Max Planck Schools in which LMU Munich participates

    • Max Planck School Matter to Life
    • Max Planck School of Cognition
    • Max Planck School of Photonics

    Helmholtz Graduate School in which LMU Munich participates

    • HELENA - Helmholtz Graduate School Environmental Health

    Munich School for Data Science in which LMU Munich participates

    • MUDS – Munich School for Data Science

    ENB Doctorate Program in which LMU Munich participates

    • Rethinking Environment: The Environmental Humanities and the Ecological Transformation of Society (Elite Network of Bavaria: International Doctorate Program)

    BayWISS-Verbundkollegs in which LMU Munich participates

    • BayWISS-Kolleg Health
    • BayWISS-Kolleg Life Sciences and Green Technologies
    • BayWISS-Kolleg Sozialer Wandel

    Marie Skłodowska-Curie Innovative Training Networks (ITN) in which LMU Munich participates

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    Munich School for Data Science

    Apply now / new graduate school for Data Science in Munich

    Poster

    Become the data scientist of tomorrow – in biomedicine, fusion research, robotics  or geo-research! Apply now for a PhD position at:

    www.mu-ds.de

    The new graduate school for Data Science was founded by the Max Planck Institute for Plasma Physics, the Helmholtz Zentrum München, the German Aerospace Center, the Technical University of Munich  and the Ludwig Maximilian University of Munich. The Leibniz Supercomputing Center and the Max Planck Computing & Data Facility, two major computing and data centers in the Munich region, are also associated. More >> Registration is open until 28 February 2019 .

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    Technical University of Munich

    • TUM Graduate School
    • Technical University of Munich

    Technical University of Munich

    Doctorate at the Technical University of Munich

    Doctoral candidates at TUM work on challenging academic questions , and are supported by prominent researchers. TUM Graduate School encourages an environment in which academic knowledge and professional qualification are perfectly interwoven. On the following pages, you will find all the information you need about doing a doctorate ​​​​​​​ at TUM.

    phd data science munich

    Doctoral Candidates

    phd data science munich

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    phd data science munich

    About TUM Graduate School

    phd data science munich

    30.04.2024 Call for applications - Hermann Eiselen Science Award

    15.01.2024 Call for Entries - Eppendorf Award 2024

    31.12.2023 Ausschreibung: Roman Herzog Forschungspreis Soziale Marktwirtschaft

    Courses & Events

    16.01.2024 Special Kick-Off Seminar on 16 January 2024

    29.11.2023 Fireside Chat: Are we equipped for tomorrow? Future skills in a transforming world.

    28.11.2023 Evonik MChG Day 2023

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    Technical University of Munich

    • Munich Data Science Institute
    • Technical University of Munich

    Technical University of Munich

    Linde/MDSI Doctoral Fellowships

    Linde logo with slogan: "Making our world more productive"

    Linde and the MDSI have partnered to promote excellent PhD fellows across different fields to strengthen interdisciplinary research addressing data science challenges. The Linde/MDSI PhD Fellows are essential to MDSI's thriving and dynamic research atmosphere. They participate in the specially tailored MDSI training program and are co-located at the institute's facilities as needed. MDSI strongly supports their collaboration and interaction with fellows and faculty from other research areas.

    Call for Applications

    Annually, MDSI launches calls for applications to recruit new fellows from the areas of data science, machine learning, and artificial intelligence, their mathematical foundations, and their application in the various scientific fields represented at TUM. To apply, doctoral candidates outline their interest in the PhD thesis and connection to the above research areas in a motivation letter. Furthermore, they compose a brief research plan describing their ideas for the thesis topic separately.

    Before applying, the doctoral candidates reach out to their potential thesis supervisors at TUM. The successful applicants to the Linde/MDSI PhD Fellowship program receive half of the funds for their position from MDSI - the other half must be co-funded by the host.

    TUM External Applicants

    Individuals who still need to start working at TUM must establish contact with a chair at TUM before applying for this program to secure funding for their PhD position. This process may take a considerable amount of time. Therefore, it is advisable to approach potential hosts well in advance before applying.

    Eligibility

    General requirements:

    • Excellent master’s degree (or equivalent) in computer science, mathematics, engineering, natural sciences, or other data science-related social disciplines.
    • General admission requirements for a doctorate at TUM are met as defined here .
    • Membership in the TUM Graduate School (as per supervision agreement) cannot have started before the application deadline of the respective call.

    Please provide the following documents:

    • CV including a list of publications and awards (if applicable).
    • Scanned transcripts of certificates (bachelor’s degree, master’s degree including transcript of records, other degrees, or awards).
    • Motivation letter as described above (max. 500 words).
    • Research plan as described above (max. 500 words).
    • Names and addresses of two references who can provide letters of recommendation.
    • Support letter of the chair who is willing to act as a host. In this letter, the host agrees to supply one-half of the PhD funds.

    Details, including deadlines and MDSI contact, will be provided in the annual call's specific documentation.

    The next call for applications is open. The deadline for applications is 7 January 2024 .

    Detailed information on the call and the application process is provided in this document:  Linde_MDSI_PhD_Fellowships_23.pdf .

    Furthermore, we require the submission of a signed support letter:  Linde_MDSI_PhD_Fellowships_23_LoI.pdf .

    phd data science munich

    [email protected]

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    PhD Positions (f/m/x) in Data Science

    phd data science munich

      PhD Positions (f/m/x) in Data Science

    The  Munich School for Data Science (MUDS)  is a joint initiative of Helmholtz Munich, Max Planck Institute of Plasma Physics, and the German Aerospace Center with the Ludwig-Maximilians-Universität München and the Technical University of Munich as well as with the Leibniz Supercomputing Center and the Max Planck Computing and Data Facility, and an increasing number of industrial partners.

    MUDS is offering PhD positions (f/m/x) for students with a background in data science, computer science, computational science, or a domain science with a strong focus on computational science, and an interest in training at the interface of data science and the scientific domains pursued at the three participating Helmholtz centers.

    Methodologically, it will cover a broad range of topics, from large-scale data management to data mining and data analytics (including machine learning and deep learning), from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty quantification, model-order reduction, or multi-fidelity methods. The primary fields of application are biomedicine, earth observation and robotics. Consequently, a MUDS student will learn to

    (i) develop and adapt state-of-the-art methods from data science and (ii) apply the acquired knowledge to the research domains of the respective Helmholtz centers.

    The research will be accompanied by scientific and transferable and professional skills workshops, summer schools and events, as well as an international lab research stay, thus enabling them to become the outstanding data scientists of tomorrow.

    The application deadline is  November 20, 2023. For more information and to apply , please visit  https://www.mu-ds.de

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    International Programmes 2023/2024

    phd data science munich

    PhD Programme in Biomedical Data Science PhD Programme in Biomedical Data Science

    Hannover medical school • hannover.

    • Course details
    • Costs / Funding
    • Requirements / Registration
    • Leibniz University Hannover
    • Helmholtz Institute for Infection Research Braunschweig
    • Technical University Braunschweig
    • University of Veterinary Medicine Hannover
    • Ostfalia University
    • Fraunhofer Institute
    • Several other research institutions in the Hannover region

    German classes are offered.

    Digitisation and advances in data science, including artificial intelligence (AI), which influence and change all areas of life, have a particular impact on life sciences and health-related sciences. For example, large data sets for each individual patient are already routinely collected and systematically recorded. A further increase in complexity is expected in the coming years due to increasing use of molecular and imaging diagnostics. The degree of resolution – already at single-cell level – will continue to increase in all disciplines of life sciences, and the need to process and combine huge data sets such as the phenome, genome and exposome, including continuously measured health data such as heartbeat or activity measurements of wearables, will increase. The processing and analysis of such complex data is one of the greatest challenges for life sciences, and in particular, for health-related sciences. However, there are few experts, and application is limited and constrained by the scientific environment, which hinders the full use of existing and expected data. As part of the Translationsallianz in Niedersachsen (TRAIN), which integrates various regional partners from translational research, the concept of a cross-university PhD programme involving non-university institutions was developed to enable the combination of different scientific and technological disciplines relevant to biomedical data science. The start of "BIOMEdical DAta Science (BIOMEDAS)" took place in the winter semester 2020 at Hannover Medical School (MHH), which is the leading institution of the new programme of the Hannover Biomedical Research School (HBRS). BIOMEDAS is directed to students who are interested in combining disciplinary knowledge with the skills of a data scientist and working at the interface of bioinformatics, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners are further developed in different areas, which open up numerous opportunities for interdisciplinary exchange. In particular, projects in the areas of “exploiting the potential of available biomedical and clinical data sources“, “making use of biomedical data to realise personalised medicine”, “understanding pathomechanisms through biomathematical modelling” and “employing artificial intelligence to develop tailored diagnostic and treatment strategies” will be researched by BIOMEDAS students. The PhD programme applies a collaborative training principle involving supervisors from the individual partners. Annual meetings with the thesis advisory committee and a combination of a core research project and individual courses form the basis of the training programme.

    The course is organised similarly to all other programmes in Hannover Biomedical Research School. https://www.mhh.de/hbrs  

    • International guest lecturers
    • Specialist literature in other languages
    • Language training provided
    • Training in intercultural skills
    • Study trips
    • Projects with partners in Germany and abroad

    About 400 EUR per semester

    About 1,000 EUR

    All PhD students are financially supported, usually by means of the respective supervisor.

    BIOMEDAS is addressed to students who are interested in combining disciplinary knowledge with skills in biomedical data science. These can be either computer scientists or life scientists who already have a training in bioinformatics and are interested in developing their career in biomedical data science.

    In order to be registered to the PhD programme, a successfully completed university degree in computer science related fields (e.g. medical computer science, bioinformatics, physics, engineering, computer science, statistics, mathematics) or in health science related fields (e.g. medicine, veterinary medicine, pharmacy, life sciences) is mandatory. Applicants from the field of computer science have to demonstrate an adequate understanding of biomedical research, while applicants from the field of health sciences have to demonstrate competence in data science. The proof must be submitted to the programme commission, which may propose further qualification measures in consultation with the supervisor.

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    phd data science munich

    Welcome to the website of the doctoral program "Statistics: Theory and Methods of Empirical Modeling" of the Department of Statistics at the LMU in Munich.

    Our main goal is to provide doctoral candidates with a perspective on the methodical foundations of Statistics that goes far beyond a specialization in the life, social or economic sciences or the humanities and to . institutionalize a scientific dialogue through interdisciplinary applications. This is to ensure that, going forward, we can rely on a common academic foundation and language as well as a diversity of methods for the description and modeling of uncertainty in various applications. 

    Contact 

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    Ludwig-Maximilians-Universität München Department of Statistics  Ludwigstraße 33 80539 München

    Speaker of the doctoral program  

    Prof. Dr. Göran Kauermann

    Coordination of the doctoral program

    Dr. Michael Windmann

    13.10.2016: JOURNALS CLUB

    • November 8th, 2016: Fabian Scheipl: S. Wood, N Pya, B Säfken, Smoothing parameter and model selection for general smooth models abstract at arxiv.org
    • December, 6th, 2016: Malte Kurz, tba

    February, 7th, 2016: Georg Schollmeyer, tba

    time: 16:00 c.t. location: all talks take place in the lecture room of the Statistics Department ( room 144, Seminarraum Ludwigstrße 33 )

    13.10.2016: SUMMER RETREAT 2017

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    Master of Science (M.Sc.)

    Data Engineering and Analytics

    “Big Data” is the driving force behind groundbreaking developments – from machine learning to autonomous vehicles and biotechnology. Students in this program learn to manage, analyze and process very large amounts of data using innovative computer science techniques.

    Course Homepage

    • 4 semesters (fulltime)

    Winter semester: 01.02. – 31.05. Summer semester: 01.09. – 30.11.

    • Aptitude Assessment for Master
    • Possible for both winter and summer semester
    • Student Fees: 85.00 €
    • Tuition fees for international students

    Information on Degree Program

    Program profile.

    Handling and analyzing very large amounts of data is an urgent problem in many areas of science and industry and requires novel approaches and techniques. The trend towards “Big Data” is caused by a host of developments: Firstly, the creation and storage of large data sets becomes feasible and economically viable, for example due to price decreases in storage space, sensors, smart devices, social networks and many more. Secondly, technical advances for example in multi-core systems and cloud computing make it possible to examine data sets at large scale. And thirdly, such amounts of data do not only origin in the “classical” domains like business data, but now are created in many areas of life. Consider vehicles, that create sensor data and share information via intelligent networking, or consider data that is created by intelligent energy grids.

    The master program Data Engineering and Analytics steps up to these developments and provides an education that on the one hand enables graduates to design and plan industry grade solutions in the area of Big Data, on the other hand creates a solid starting point for ventures into research.

    For a comprehensive description of the program, please refer to the degree program documentation:

    • Degree program documentation for the master's program in Data Engineering and Analytics (PDF, German)  

    The master’s programs “Mathematics in Data Science” and “Data Engineering and Analytics” offer access to many career opportunities including: research, consulting, IT security, systems design, and data science in industry. The respective departments offer Ph.D. positions that are the pathway to a career in research. Typical job profiles in industry include data analysts and data engineers. Data engineers master very large databases and distributed information systems and are responsible for IT security and applied data analytics for structuring data. Data analysts filter and extract information from large data sets based on statistical and mathematical methods and tailor them towards informed strategic decisions

    Program structure

    The program is divided into three areas of study: Data Analysis, Data Engineering and Analytics and Data Engineering. The first area is concerned with fundamentals of understanding and modelling data and the underlying relationships. Data Engineering consists of lectures about the construction of systems that perform efficient and scalable data processing, thus enable the methods of Data Analysis on large data sets.

    The curriculum comprises mandatory courses on Data Analysis and Data Engineering. Advanced lectures are offered in these area of studies: Data Engineering contains lectures about distributed systems, distributed databases, query optimization, database systems on modern CPU architectures and high performance computing.  Data Engineering and Analytics offers lectures about machine learning, business analytics, computer vision and scientific visualization. Data Analysis is concerned with topics that require solid mathematical foundations: Fundamentals of Convex Optimization, Computational Statistics and more.

    • Program structure & Overview of modules

    Language of instruction

    Required language skills for admission:

    You need sufficient English language skills if you wish to apply for this program. Evidence of your language proficiency has to be submitted before the end of the application deadline. Learn more about recognized certificates and other ways to prove your English language skills .

    This evidence of your language proficiency confirms that you comply with the minimum language requirements for admission to the program. Depending on the program and your individual background, it may be necessary for you to keep working on your language skills during your studies. Be sure to take a look at the services of our Language Center.   

    Language of instruction:

    The language of instruction for this program is usually English. This means that most of the modules are offered in English. Some courses may, however, be taught in German.To learn more about the language of instruction for each module, contact the departmental student academic advisor of this program.

    Information on study organization

    • Information on exams
    • Information on studying abroad

    Fees for the program

    The tuition fees for international students from third countries for this degree program are 6,000 euros per semester .

    Many international students can have their fees waived or receive scholarships to finance them. You can find all information on waivers and scholarships here.

    Please note: The semester fee as a contribution to the student union must be paid additionally. It varies depending on where you are studying. You can find all information on the semester fee here.

    Academic Regulations: Application, Studying and Exams

    • General Academic and Examination Regulations
    • Academic and Examination Regulations (PDF 335 KB)
    • All regulations and legal framework concerning studies

    Application and Admission

    Application process.

    Minimum requirements to apply for a Master's program at TUM are a recognized undergraduate degree (e.g. a bachelor’s) and the successful completion of the aptitude assessment procedure. Aptitude assessment allows the TUM school or department to which you are applying the opportunity to evaluate your individual talents and motivation for study.

    During the application period, you must apply through the TUMonline application portal and upload your application documents.

    If you receive an offer of admission, you will additionally have to submit individual documents as notarized hardcopies by post to be enrolled.

    Generally, applicants with a qualification for postgraduate studies (e.g. a bachelor’s) obtained outside of the EU / EEA must have their documents reviewed in advance through uni-assist.

    • Applying for a master’s program: Application, admission requirements and more  
    • Important information about your application from the TUM school or department

    Documents required for the online application

    • Degree Certificate and Diploma or Subject and Grade Transcript of Studies to Date
    • Transcript of Records
    • Proof of English Language Proficiency
    • Letter of Motivation
    • Curriculum (e.g. module description)
    • Curricular Analysis
    • Complete and Current Résumé
    • Preliminary Documentation (VPD) if the qualification for graduate studies (e.g. a bachelor's) is obtained outside the EU/EEA

    We may require additional documents depending on your educational background and your country of origin . Complete the online application to receive a comprehensive list of the required documents. 

    Documents required for enrollment

    • Application for Enrollment (signed)
    • Degree Certificate and Diploma (certified copy)
    • Transcript of Records (certified copy)
    • Most Current Photo (as for ID)
    • Digital notification of your health insurance status from a German public health insurance provider (requested by applicant)

    We may require additional documents depending on the type of educational background you earned and your country of origin . After accepting an offer of admission in TUMonline, you will receive a list of documents you must submit to TUM in hardcopy for enrollment.

    Application deadlines

    Application period for winter semester: 01.02. – 31.05. Application period for summer semester: 01.09. – 30.11.

    During the application period, you must apply through the TUMonline application portal and upload your application documents. Please be aware that we can only process your application if you upload all required documents within the application period.

    We will review your application as soon as it is complete. Please check your TUMonline account regularly, to see if we have any queries to your documents or if you have to amend one or more documents.

    After receiving admission, you will see in TUMonline which documents you have to submit for enrollment , and in which form. Please note that you always have to send the signed application for enrollment and all notarized hardcopies by post .

    We recommend that you submit the documents for enrollment as soon as possible after receiving admission. If individual documents are not available by then, you can submit them up to 5 weeks after the start of the lecture period. You will, however, only be enrolled once we have received all documents .

    You can check the status of your application at any time in your TUMonline account.

    Admission process

    Selection takes place through an aptitude assessment procedure. Aptitude assessment is a two-part procedure after the submission of an official application to a program. In this procedure, the TUM school or department determines whether you meet the specific requirements for its master’s degree program.

    In the  initial stages , the grades you obtained during your bachelor's program, as well as your written documents, will be evaluated using a  point system . Depending on the  amount of points accumulated , applicants are either  immediately admitted ,  rejected  or invited to an  admissions interview . 

    • Description of the Aptitude Assessment (German) (PDF 323 KB)

    Information

    Questions about application and admission

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    Munich School for Data Science (MUDS) Research Program in Germany

    Opportunity Forum

    Deadline: November 20, 2023

    Applications are open for several PhD potions in data science at Munich School for Data Science in Germany, Munich. The Munich School for Data Science (MUDS) PhD positions are open to for students of both Domestic and intonations status , who have a background in the following fields.

    • Computer science,
    • Data science
    • Biomedicine,
    • Plasma physics,
    • Earth observation and
    • Robotics with a very strong focus in computer science, data science or similar

    MUDS aims to train doctoral candidates with specializations in data science and the scientific domains pursued at the three participating Helmholtz centers. Topics and projects will range from large-scale data management to data mining and data analytics, combined with machine learning and deep learning . From high-performance computing to high-performance analytics, from data integration to data-related topics such as uncertainty quantification, model-order reduction, or multi-fidelity methods.

    Munich School for Data Science (MUDS) is a joint initiative of the three Helmholtz centers in the Munich area ( Helmholtz Zentrum München, Max Planck Institute of Plasma Physics, German Aerospace Center ) with the Ludwig-Maximilians-Universität München (LMU) and the Technical University of Munich (TUM) as well as with the Leibniz Supercomputing Center (LRZ) and the Max Planck Computing and Data Facility (MPCDF)

    Accepted applicants will be eligible for the following benefits

    • There is no tuition fee for any of the programmes offered at MUDS and
    • PhD students receive financing throughout their PhD studies
    • In case you are invited to an on-site interview, be reimbursed for your travel expenses

    Eligibility

    Candidates for the PhD position must meet the following conditions

    • Applicants from all nationalities are welcome to apply for these positions
    • You must have graduated with a university master’s degree (MSc or equivalent) from a relevant discipline to apply.
    • To enroll at one of Munich’s universities (TUM or LMU) a master’s thesis must have been written during Master’s studies.
    • In case you haven’t finished your master’s degree by the application deadline, you may provide a provisional certificate or bona fide statement from the university stating the marks already obtained and an estimated graduation date.
    • You will only be considered and accepted for the program after successfully completing your master’s degree

    Application

    Applications are submitted online using the program application portal . Applicants need to submit the following documents with their application

    • Your Master Diploma, certificate and transcript of records in German or English
    • You must also submit your Bachelor Diploma, certificate and transcript of records in German or English
    • If your certificates were not issued in English, you must include an original AND official English translation
    • Submit your High School Certificate
    • The applicant’s most recent Curriculum Vitae (as a PDF document)
    • Request two (2) letters of recommendation to be submitted directly by the Referees
    • You must also provide proof of English Language proficiency speakers in case you are non-native Speaker

    To apply, cli c k here

    For more information, visit the official website here

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    Apply to PhD program in data science at Munich School for Data Science in Germany

    by Samrach · April 4, 2022

    phd data science munich

    The deadline for applications is April 26, 2022.

    The  Munich School for Data Science  (MUDS) has open PhD positions for students with a background in computer science, data science or similar, or one of the domain sciences biomedicine, plasma physics, earth observation and robotics with a very strong focus in computer science, data science or similar, or interdisciplinary study programs combining both (e.g. geoinformatics, bioinformatics).

    MUDS is a joint initiative of the three Helmholtz centers in the Munich area (Helmholtz Zentrum München, Max Planck Institute of Plasma Physics, German Aerospace Center) with the Ludwig-Maximilians-Universität München (LMU) and the Technical University of Munich (TUM) as well as with the Leibniz Supercomputing Center (LRZ) and the Max Planck Computing and Data Facility (MPCDF), and works together with an increasing number of industrial partners.

    The aim of MUDS is to train doctoral candidates at the interface of data science and the scientific domains pursued at the three participating Helmholtz centers. Methodologically, it covers a broad range of topics, from large-scale data management to data mining and data analytics (including machine learning and deep learning), from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty quantification, model-order reduction, or multi-fidelity methods. The primary fields of application are biomedicine, plasma physics, earth observation and robotics. Consequently, a MUDS student will learn to

    (i) develop and adapt state-of-the-art methods from data science and

    (ii) apply the acquired knowledge to the research domains of the respective Helmholtz centers.

    Our goal is to establish an internationally visible graduate school that attracts excellent candidates who are interested in interdisciplinary training specifically tailored to the needs of their individual projects. Their research will be accompanied by scientific and transferable skills workshops, summer schools and events, as well as an international lab research stay, enabling them to become the outstanding data scientists of tomorrow.

    Official website

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    Computational Data Science

    Online Graduate Certificate

    Be a Game Changer

    Learn computational data science to harness the power of big-data, your pathway to the ai workforce.

    Organizations know how important data is, but they don’t always know what to do with the volume of data they have collected. That’s why Carnegie Mellon University designed the online Graduate Certificate in Computational Data Science Foundations; to teach technically-savvy professionals how to leverage AI and machine learning technology for harnessing the power of large scale data systems.   

    Computer-Science Based Data Analytics

    When you enroll in this program, you will learn foundational skills in computer programming, machine learning, and data science that will allow you to leverage data science  in various industries including business, education, environment, defense, policy and health care. This unique combination of expertise will give you the ability to turn raw data into usable information that you can apply within your organization.  

    Throughout the coursework, you will:

    • Practice mathematical and computational concepts used in machine learning, including probability, linear algebra, multivariate differential calculus, algorithm analysis, and dynamic programming.
    • Learn how to approach and solve large-scale data science problems.
    • Acquire foundational skills in solution design, analytic algorithms, interactive analysis, and visualization techniques for data analysis.

    An online Graduate Certificate in Computational Data Science from Carnegie Mellon will expand your possibilities and prepare you for the staggering amount of data generated by today’s rapidly changing world. 

    A Powerful Certificate. Conveniently Offered. 

    The online Graduate Certificate in Computational Data Science Foundations is offered 100% online to help computer science professionals conveniently fit the program into their busy day-to-day lives. In addition to a flexible, convenient format, you will experience the same rigorous coursework for which Carnegie Mellon University’s graduate programs are known. 

    For Today’s Problem Solvers

    This leading certificate program is best suited for:

    • Industry Professionals looking to deliver value to companies by acquiring in-demand data science, AI, and machine learning skills. After completing the program, participants will acquire the technical know-how to build machine learning models as well as the ability to analyze trends.
    • Recent computer science degree graduates seeking to expand their skill set and become even more marketable in a growing field. Over the past few years, data sets have grown tremendously. Today’s top companies need data science professionals who can leverage machine learning technology.   

    At a Glance

    Start Dates January 2024 May 2024

    Application Deadlines Rolling Admissions

    We are still accepting applications to start in Spring 2024 for a limited number of remaining spots. Apply today to secure your space in the program.

    Program Length: 12 months

    Program Format: 100% online

    Live-Online Schedule: 1x per week for 90 minutes in the evening

    Taught By: School of Computer Science

    Request Info

    Questions? There are 2 ways to contact us. Call 412-501-2686 or send an email to  [email protected]  with your inquiries .

    Looking for information about CMU's on-campus Master of Computational Data Science degree? Visit the program's website to learn more.  Admissions consultations with our team will only cover the online certificate program.

    A National Leader in Computer Science

    Carnegie Mellon University is world renowned for its technology and computer science programs. Our courses are taught by leading researchers in the fields of Machine Learning, Language Technologies, and Human-Computer Interaction. 

    phd data science munich

    Number One  in the nation for our artificial intelligence programs.

    phd data science munich

    Number One  in the nation  for our programming language courses.

    phd data science munich

    Number Four  in the nation for the caliber of our computer science programs.

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    1. bioinformatics VLOG • FINISHED my phd • coding, setup + office days 💻☁️🌱

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    COMMENTS

    1. MUDS

      The Munich School for Data Science (MUDS) has open PhD positions for students with a background in computer science, data science or similar, or one of the domain sciences biomedicine, plasma physics, earth observation and robotics with a very strong focus in computer science, data science or similar, or interdisciplinary study programs combinin...

    2. Doctoral Studies

      Munich Data Science Institute Technical University of Munich Home Education Doctoral Studies Doctoral Studies For PhD students at TUM whose research projects are related to data science issues, MDSI offers various funding and qualification opportunities.

    3. Apply now

      Application Apply now Become a data scientist, apply to PhD program in data science at Munich School for Data Science in Germany, Munich (Photo: MUDS) The deadline for applications is Nov 20, 2023.

    4. Doctoral Program

      The activities can be registered in TUM Graduate School's DocGS. Registration and further Information ... Munich Data Science Institute (MDSI) TU Munich. Walther-von-Dyck-Straße 10 (GALILEO Garching) 85748 Garching bei München. [email protected] Tel.: +49 89 289 52320. Top News

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      The Munich Data Science Institute The digital revolution is transforming societies, economies, and even science and its paths to knowledge. At the Munich Data Science Institute (MDSI), we are anticipating, accompanying and shaping this change.

    6. Munich School for Data Sciences (MUDS)

      Munich School for Data Sciences (MUDS) The aim of the Munich School for Data Science (MUDS) is to educate the next generation of Data Scientists at the interface of data science and four different application areas: Biomedicine, Plasma Physics, Earth Observation, and Robotics.

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      MUDS - München Analyzing gene sequences to predict diseases or developing robots that monitor their own health - research at the Munich School for Data Science (MUDS) has many facets. Top Location for Computational Sciences

    8. Application Procedure

      Application period: Oct 20 - Nov 20, 2023 Deadline for referees: Nov 22, 2023 Invitation for online interview: mid-January, 2024 Interview symposium (online interviews): early February 2024 Decision: March 2024 Eligibility Applicants require an university master's degree (MSc or equivalent) from a relevant discipline to apply.

    9. Study

      Munich Data Science Institute (MDSI) TU Munich. Walther-von-Dyck-Straße 10 (GALILEO Garching) 85748 Garching bei München. [email protected] Tel.: +49 89 289 52320. Top News 22.01.2024 MDSI Cloud Computing Event 18.01.2024 Show & Tell Workshop with Bayerischer Rundfunk on AI models and training data for journalism use cases ...

    10. Graduate School for Data Science

      This data holds a great amount of potential - if it can be used effectively. To this purpose the newly founded Munich School for Data Science @ Helmholtz, TUM & LMU (MuDS) will train new researchers in this field. The aim of the Graduate School is to make big data useable. That means, that huge amounts of data must be analysed and interpreted.

    11. ESG Data Science

      The elite program Data Science is an interdisciplinary program and is carried out jointly by the Department of Statistics and the Institute for Informatics at LMU Munich. The program is part of and is supported by the Elite Network of Bavaria. The curriculum of the elite master program Data Science is a modularised study program.

    12. Doctoral Fellowships

      Linde and the MDSI have partnered to promote excellent PhD fellows across different fields in order to strengthen interdisciplinary research addressing data science challenges. The Linde/MDSI PhD Fellows are an essential part of MDSI's thriving and dynamic research atmosphere. ... Munich Data Science Institute (MDSI) TU Munich. Walther-von-Dyck ...

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      print Doctoral Programs LMU Munich offers a broad range of doctoral programs as well as some umbrella structures. In addition, the university cooperates with other institutions on a doctoral level.

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      The new graduate school for Data Science was founded by the Max Planck Institute for Plasma Physics, the Helmholtz Zentrum München, the German Aerospace Center, the Technical University of Munich and the Ludwig Maximilian University of Munich. The Leibniz Supercomputing Center and the Max Planck Computing & Data Facility, two major computing ...

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      TUM Graduate School is the central institution for Ph.D. applicants, Ph.D. candidates and supervisors at the Technical University of Munich. ... Hermann Eiselen Science Award 15.01.2024 Call for Entries - Eppendorf Award 2024 31.12.2023 Ausschreibung: Roman Herzog Forschungspreis Soziale Marktwirtschaft ...

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      Linde and the MDSI have partnered to promote excellent PhD fellows across different fields to strengthen interdisciplinary research addressing data science challenges. The Linde/MDSI PhD Fellows are essential to MDSI's thriving and dynamic research atmosphere. ... Munich Data Science Institute (MDSI) TU München. Walther-von-Dyck-Straße 10 ...

    17. Open PhD Positions in Responsible Data Science at TU Munich

      Requirements: A Master's degree (or equivalent) in Computer Science, Statistics, Mathematics, or related fields. Knowledge of machine learning, data mining, or related fields. Excellent communication skills and ability to work in a collaborative team environment. The PhD positions will be based at the Technical University of Munich, Germany.

    18. PhD Positions (f/m/x) in Data Science job with Munich School for Data

      PhD Positions (f/m/x) in Data Science. The Munich School for Data Science (MUDS) is a joint initiative of Helmholtz Munich, Max Planck Institute of Plasma Physics, and the German Aerospace Center ...

    19. PhD Programme in Biomedical Data Science

      These can be either computer scientists or life scientists who already have a training in bioinformatics and are interested in developing their career in biomedical data science. In order to be registered to the PhD programme, a successfully completed university degree in computer science related fields (e.g. medical computer science ...

    20. Doctoral Program

      Our main goal is to provide doctoral candidates with a perspective on the methodical foundations of Statistics that goes far beyond a specialization in the life, social or economic sciences or the humanities and to . institutionalize a scientific dialogue through interdisciplinary applications.

    21. Data Engineering and Analytics

      The master's programs "Mathematics in Data Science" and "Data Engineering and Analytics" offer access to many career opportunities including: research, consulting, IT security, systems design, and data science in industry. ... Preliminary Documentation (VPD) if the qualification for graduate studies (e.g. a bachelor's) is obtained ...

    22. Munich School for Data Science (MUDS) Research Program in Germany

      811 Deadline: November 20, 2023 Applications are open for several PhD potions in data science at Munich School for Data Science in Germany, Munich. The Munich School for Data Science (MUDS) PhD positions are open to for students of both Domestic and intonations status, who have a background in the following fields. Computer science, Data science

    23. Apply to PhD program in data science at Munich School for Data Science

      The Munich School for Data Science (MUDS) has open PhD positions for students with a background in computer science, data science or similar, or one of the domain sciences biomedicine, plasma physics, earth observation and robotics with a very strong focus in computer science, data science or similar, or interdisciplinary study programs combinin...

    24. CMU's Online Graduate Certificate in Computational Data Science

      The online Graduate Certificate in Computational Data Science Foundations is offered 100% online to help computer science professionals conveniently fit the program into their busy day-to-day lives. In addition to a flexible, convenient format, you will experience the same rigorous coursework for which Carnegie Mellon University's graduate ...