Ph.D. Student for AI in Infection Research (COVID-19) (m/f/d, E 13 TV-L, 65%)

University of Tuebingen
Computer Science
Germany Baden-Wuerttemberg Tuebingen


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 German government, is currently looking for a

Ph.D. Student for AI in Infection Research (COVID-19) (m/f/d, E 13 TV-L, 65%)

starting as soon as possible.

Our research group has extensive knowledge at the interface between statistical machine learning, digital medicine, and computational biology, and is a contributor to the excellence cluster “Machine Learning: New Perspectives for Science” where Nico is a PI.

We develop methods that allow answering new biomedical questions (Ünal et al. 2021, AAAI; Roeder et al. 2019, Nucleic Acids Research), optimize them in close contact with our excellent national and international biomedical partners (Mendoza et al. 2018, Nature; Kreer et al. 2020, Cell; Vanshylla et al. 2021, Cell Host and Microbe), and are involved in efforts for robust reproducible AI in medicine (Blumenthal et al. 2021, Nature Methods).

About the project

The position will be available upon final grant approval within the EuCARE project, a multidisciplinary interconnected effort to provide robust, data driven evidence to deal with SARS-CoV-2 variants and the COVID-19 epidemic focusing on hospital patients, vaccinated healthcare workers and schools’ cohorts, with the support of strong immuno-virological and artificial intelligence (AI) components.

The overall aims of the project are:

to elucidate the relations among different circulating variants, available vaccines and host immune response
to analyze the clinical course of COVID-19 in patients in relation to the circulating variants of concern in order to deliver recommendations for optimized clinical management and treatment
to deliver recommendations on the best strategies to control viral spread with specific reference to the school setting, in relation to the circulating variants of concern
The initial fixed-term contract will have a duration of 3 years with possible extension.
Application deadline: 24th October 2021.


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, C/C++, R, Matlab, JavaScript, Java) and knowledge of ML frameworks (PyTorch, TensorFlow, etc.)
a keen interest in interdisciplinary work
proficiency in English
Other relevant qualifications include:

background in Data Science, Machine Learning or Statistics
experience with analysis of virus sequence, medical data (clinical data, molecular data, etc.), and/or high-throughput data (next-generation sequencing)
knowledge of databases (MySQL, NoSQL)
We are committed to enhancing diversity in science, and particularly looking forward to receiving applications from women, non-binary people and researchers from underrepresented groups across cultures, genders, ethnicities, and lifestyles. In case of equal qualification and experience, physically challenged applicants are given preference. We actively promote the compatibility of science / work / studies / family life and care work. The employment will be carried out by the central administration of the University of Tübingen.

Start date

As soon as possible

How to Apply

Please send your application (including your motivation letter, curriculum vitae, certificates, and academic references) with the subject Application Ph.D. Student COVID-19 via e-mail to Prof. Dr. Nico Pfeifer:

Application deadline: 24th October 2021.