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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    
Ph.D. Student in Biomedical Data Science (E13 TV-L, 65%)   
starting as soon as possible. The initial fixed-term contract will be for 3 years with possible extension.   
The group has extensive knowledge at the interface between statistical machine learning, digital medicine, and computational biology. 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, Scheid et al. 2016, Nature, Döring et al. 2016, Retrovirology, Caskey et al. 2017, Nature Medicine).   
The ideal candidates will have a M.Sc. or equivalent in Biomedical Data Science, Biometry, Biostatistics, Bioinformatics, Medical Informatics, Computer Science, Computational Biology or a related life science discipline. The applicants should have an interest in interdisciplinary work. 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 
• Experience with medical data (clinical data, molecular data, …) 
• Experience with high-throughput data (next-generation sequencing, mass spectrometry)  
• Databases (MySQL, NoSQL) 
• Privacy-preserving machine learning  
Knowledge of the adaptive immune system is a plus.  
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 as a single PDF to Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! (subject: Ph.D. student application (Biomedical Data Science)) by May 7th.