Karriere
am Klinikum & Medizinischer Fakultät
PhD Position in Computational Psychiatry / Machine Learning (f/m/d)
Faculty of Medicine Tübingen, Kaufmann Lab, index number 7641
Part-time: 65 %
Limited: 3 years 1
Start of work:
as soon as possible
Application deadline: 09.07.2026
TV-L
i.d.R. E13 2
- Data curation, processing and statistical analysis
- Development of machine learning models
- Scientific writing and presentation
- Collaborative, interdisciplinary research exchange
- Master degree in the field of computational neuroscience, data science or a related field
- Excellent coding skills and expertise with high performance computing in big data
- Solid knowledge of multivariate statistics
- Idealy, the candidate also brings specific expertise with analysis of neuroimaging data and/or expertise with mental health / psychiatry research
- Fluency in written and spoken English, strong motivation and scientific rigor
Modern Environment
- innovative university hospital
- state-of-the-art technology
- world-class international research
- excellent career prospects
Research
- cutting-edge research at the highest level
- support from PhD to professorship
Career & Development
- structured onboarding
- in-house academy
- diverse training opportunities
- targeted career development
Internationality
- cultural & generational diversity
- support through language courses
- integration programmes (nursing)
Equal Opportunities & Diversity
- active promotion of equality
- internal committees as a point of contact
- network for conflict resolution
- innovative university hospital
- state-of-the-art technology
- world-class international research
- excellent career prospects
- cutting-edge research at the highest level
- support from PhD to professorship
- structured onboarding
- in-house academy
- diverse training opportunities
- targeted career development
- cultural & generational diversity
- support through language courses
- integration programmes (nursing)
- active promotion of equality
- internal committees as a point of contact
- network for conflict resolution
The Faculty of Medicine is one of the four founding faculties of the Eberhard Karls University of Tübingen. With its non-clinical facilities as well as its research and teaching area corresponding to the organisational units of the University Hospital, it is one of the largest medical training and research institutions in Baden-Württemberg.
The PhD candidate will be part of the Neurotechnology and Computational Psychiatry group at University of Tübingen (PI: Prof. Tobias Kaufmann) and supervised jointly with Prof. Peter Dayan, director of the Max Planck Institute for Biological Cybernetics. The position is part of the Else Kröner Medical Scientist College ‘Artificial intelligence for clinical brain research’ and targets computational advances in disease progression modelling. Specifically, the candidate will deploy novel machine learning models that combine large-scale datasets from biobanks with well-characterized clinical data sets, learning patterns in neuroimaging data that can be leveraged for clinical prediction.
Prof. Tobias Kaufmann
chiuyi.lam@med.uni-tuebingen.de
Prof. Tobias Kaufmann
Index number: 7641
Including CV and cover letter
Application deadline: 09.07.2026
Index number: 7641
Including CV and cover letter
Application deadline: 09.07.2026
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We offer remuneration in accordance with TV-L (collective wage agreement for the Public Service of the German Federal States),
severely handicapped persons with equal qualifications are given preferential consideration.
Interview expenses are not covered.
Please note the applicable vaccination regulations.
The employer actively promotes equal opportunities and particularly encourages applications from women.
1 Continued employment will be sought whereever possible.
2 The data provided does not constitute a basis for an employment contract at the University Hospital of Tübingen. It is intended to serve as a rough guide for all interested parties. Remuneration is governed by the applicable collective bargaining agreements in conjunction with the corresponding pay scales. Further information can be found here.
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