Ph.D. Position for Privacy-Preserving Machine Learning on Omics Data


Prof. Dr. Nico Pfeifer’s Chair for Methods in Medical Informatics, Department of Computer Science at the University of Tübingen, distinguished as excellent by the Federal Government of Germany, is inviting applications for a

3-year Research Position as a Ph.D. Student for Privacy-Preserving Analytics in Medicine (f/m/d, E13 TV-L, 65%)

starting as soon as possible.

About the project
The position is available within the Privacy-Preserving Analytics in Medicine (PrivateAIM) project, a multidisciplinary interconnected effort to develop the next-generation federated machine learning (ML) and data analytics platform within the Medical Informatics Initiative.

As a Ph.D. Student, you will be hosted at Pfeifer lab. We have extensive knowledge at the interface between statistical machine learning, digital medicine, and computational biology. Prof. Nico Pfeifer is a PI at the Cluster of Excellence Machine Learning: New Perspectives for Science, a fellow of the International Max Planck Research School for Intelligent Systems, and receives further funding through the Tübingen AI Center.

Our offer
What this position offers you:
• conducting research at a highly renowned university,
• collegial work atmosphere,
• remuneration in accordance with the TV-L (collective agreement for public employees of the German federal states) as well as all corresponding benefits,
• international collaboration opportunities,
• local & global networking opportunities incl. conferences, workshops, summer schools, etc.
• 30 days/year of paid vacation,
• flexible working hours,
• career mentoring,
• extensive visa and onboarding assistance,
• discounted public transportation, etc.
We value diversity in science, and particularly look forward to receiving applications from women, non-binary people and researchers from underrepresented groups across cultures, genders, ethnicities, and lifestyles. We actively promote the compatibility of science, work, studies, family life and care work. In case of equal qualification and experience, physically challenged applicants are given preference.


The ideal candidate will have:
• a university degree (M.Sc. or equivalent) in Medical Informatics, Machine Learning, Bioinformatics, Computer Science, or a related discipline
• strong programming/scripting skills (Python, R, C++, Java) and knowledge of ML frameworks (PyTorch, Keras, etc.)
• a keen interest in interdisciplinary work
• proficiency in English
• experience in Data Science, Machine Learning or Statistics
• experience in the analysis of medical data or high-throughput data (multi-omics)

Start date

As soon as possible

How to Apply

Please send your application (including your motivation letter, curriculum vitae, certificates, and contact details of 2 academic references) with the subject “Application PhD PrivateAIM” via e-mail to Prof. Dr. Nico Pfeifer:

Application deadline: 27th November 2023.


Nico Pfeifer