Postdoctoral Research Fellow – AI & Data Science

University of Tuebingen
Computer Science


The AI & Data Science Fellowship Program, a cooperation between the University of Tübingen, distinguished as excellent by the Federal Government of Germany, and Boehringer Ingelheim, one of the leading pharmaceutical companies, is currently looking for a

Postdoctoral Research Fellow – AI & Data Science
(f/m/d, E 13 TV-L, 100%)

to work on cutting-edge and exciting AI & data science research topics that generate real added value for human and animal healthcare.

The initial fixed-term contract will start as soon as possible and have a duration of 2 years with possible extension.

About the project

The position is available within the “Learning joint representations of EHR and omics data” project, a multidisciplinary interconnected effort to provide robust, data driven evidence to deal with multi-modal biomedical data. We aim to develop cutting-edge methods that will enable better disease subtyping, disease risk prediction, and patient stratification.

As Postdoc, you will be hosted at the Pfeifer lab and collaborate with Dr. Johann De Jong of Boehringer Ingelheim as well as researchers within Cyber Valley like Carsten Eickhoff. Your host research group has extensive knowledge at the interface between statistical machine learning, digital medicine, and computational biology. Prof. Nico Pfeifer is a PI at the excellence cluster Machine Learning: New Perspectives for Science, a fellow of the IMPRS for Intelligent Systems and receives further funding through the Tübingen AI Center.

During the project, you will focus on large biobank data combining EHR and genetic information to learn the best joint representation that improves downstream analyses, including disease subtyping, disease risk prediction, and patient stratification.


The ideal candidate will have:

a Ph.D. or equivalent in Machine Learning, Medical Informatics, Bioinformatics, Computer Science, Mathematics, or a related discipline
proven experience in Data Science and Machine Learning
a competitive track record of scientific publications in leading venues
strong programming/scripting skills (Python, C++, R, Matlab, Java) and knowledge of ML frameworks (PyTorch, TensorFlow, etc.)
a keen interest in interdisciplinary work
Other relevant qualifications include:

background in Statistics
background in NLP methods
experience with analysis of medical data (clinical data, molecular data, etc.), and/or high-throughput data (next-generation sequencing)
knowledge of databases (MySQL, NoSQL)

Start date

As soon as possible

How to Apply

Please send your application (including your motivation letter, curriculum vitae, certificates, representative publications, and academic references) with the subject ”Application BI Postdoc” via e-mail to Prof. Dr. Nico Pfeifer:
Application deadline: 5th December 2022.


Prof. Nico Pfeifer