Postdoctoral Researcher (f/m/d, E13 TV-L, 100%)
Faculty of Science,Department of Computer Science
Application deadline : 21.06.2026
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 Postdoctoral Researcher Position
(f/m/d, E13 TV-L, 100%)
starting as soon as possible.
The position
The position is available within a multidisciplinary effort to develop new active substances against resistant bacteria in the project KI-gestützte Erschließung ribosomaler Naturstoffe: Ein Hochdurchsatzansatz zur Entdeckung antimikrobieller Wirkstoffe (KERN).
As a researcher, you will be welcomed at Pfeifer Lab and a vibrant campus environment in charming Tübingen. We have extensive knowledge at the interface between statistical machine learning, digital medicine, and computational biology, and plenty of collaboration opportunities beyond international borders. Nico Pfeifer is a member of the Cluster of Excellence Machine Learning: New Perspectives for Science, a PI in the Cluster of Excellence Controlling Microbes to Fight Infections, and a faculty member of the International Max Planck Research School for Intelligent Systems.
Your Responsibilities
develop a new generative AI approach for finding active substances against bacteria
collaborate closely with colleagues from mass spectrometry, infectiology and machine learning
present findings in peer-reviewed publications and international conferences
Your Profile
a Ph.D. or equivalent degree in Machine Learning, Bioinformatics, Medical Informatics, Computer Science, Mathematics, or a related discipline
strong programming/scripting skills (Python, R, C++, Java) and knowledge of ML frameworks (PyTorch, etc.)
a competitive track record of scientific publications in machine learning, ideally for generative AI methods like diffusion models
experience in Data Science and Machine Learning
experience in the analysis of high-throughput data (multi-omics)
experience with Vibe Coding is a plus
a keen interest in interdisciplinary teamwork
proficiency in English
Our Offer
conducting cutting-edge 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
life and family-friendly work conditions
career mentoring
visa and onboarding assistance
access to sports facilities, libraries, 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, professional development, family life and care work. In case of equal qualification and experience, physically challenged applicants are given preference.
How to apply
Please email your application (including your motivation letter, curriculum vitae, certificates, and contact details of 2 academic references) with the subject “Application KERN Postdoc” to Prof. Dr. Nico Pfeifer: mm-coordinator@inf.uni-tuebingen.de
Qualified Postdoc candidates will be invited to present their (previous) research (max. 30 minutes) before our selection committee and colleagues. After that, there will be time reserved for questions.
Application deadline: 21st June 2026.
- a Ph.D. or equivalent degree in Machine Learning, Bioinformatics, Medical Informatics, Computer Science, Mathematics, or a related discipline
- strong programming/scripting skills (Python, R, C++, Java) and knowledge of ML frameworks (PyTorch, etc.)
- a competitive track record of scientific publications in machine learning, ideally for generative AI methods like diffusion models
- experience in Data Science and Machine Learning
- experience in the analysis of high-throughput data (multi-omics)
- experience with Vibe Coding is a plus
- a keen interest in interdisciplinary teamwork
- proficiency in English