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The Chair for Methods in Medical Informatics (Prof. Dr. Nico Pfeifer), Department of Computer Science at Eberhard Karls University Tübingen, one of eleven German universities distinguished as excellent under the German government’s initiative, is currently looking for a


Post-doc in Biomedical Data Science (TB) (E13 TV-L, 100%)


starting as soon as possible. The initial fixed-term contract will have an end date of 31st December 2020 with possible extension.

According to WHO there were 558,000 cases of drug-resistant tuberculosis (TB) infections world-wide in 2017 of which 82% were multidrug-resistant. In this project, which is funded through a Horizon 2020 grant by the European Commission, the successful candidate will build a prediction engine that is able to provide treatment decision support for TB-infected patients by applying and extending state-of-the-art machine learning methods. This will be in close collaboration with our Western and Eastern European partners, with a focus on multidrug-resistant strains from Eastern Europe.

The group has extensive knowledge at the interface between statistical machine learning, digital medicine, and computational biology. Nico is a PI in the excellence cluster “Machine Learning: New Perspectives for Science” starting in January 2019. We are developing methods that allow answering new biomedical questions (Speicher and Pfeifer 2015, Proceedings of ISMB/ECCB 2015) and optimize them in close contact with our excellent national and international biomedical partners (Carlson et al. 2016, Nature Medicine, Schoofs et al. 2016, Science, Döring et al. 2016, Retrovirology, Mendoza et al. 2018, Nature).


The ideal candidate will have a Ph.D. or equivalent in Biomedical Data Science, Biometry, Biostatistics, Machine Learning, Bioinformatics, Medical Informatics, Computer Science, Computational Biology or a related life science discipline. Applicants should have an interest in interdisciplinary work. Proven experience in data science and machine learning as well as strong programming/scripting skills (C/C++, R, Matlab, Python, JavaScript, Java) are desirable. Other relevant qualifications include:

·       Background in Statistics

·       Proficiency in Russian language (communication with Eastern European partners)

·       Knowledge of the adaptive immune system (especially humoral immune response)

·       Experience with medical data (clinical data, molecular data, …)

·       Experience with high-throughput data (next-generation sequencing)

·       Databases (MySQL, NoSQL)

In case of equal qualification and experience, physically challenged applicants are given preference. The University of Tübingen aims at increasing the share of women in science and encourages female scientists to apply. Candidates will be officially employed by the administration of the University of Tübingen. 

Please send your application (including motivation letter, curriculum vitae, transcripts and certificates, and contact details of two academic references) via e-mail to
Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! with the subject: Post-Doc application Biomedical Data Science (TB).

Application deadline: 4th August 2019.

Candidates are encouraged to send their application material early since we will start reviewing applications already before the deadline.



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