Within an European H2020 project the Koeppl Lab at the Department of Electrical Engineering and Information Technology of Technische Universität Darmstadt, Germany invites applications, starting as soon as possible, for a

Postdoc Position – Machine Learning, Causal Inference

initially limited for 2 years, with the possibility to extend.

The multi-partner project is concerned with the assembly of high-quality medical and molecular data on paediatric cancers in order to perform ML/AI-based predictions on patient outcome and drug efficacy. The Koeppl lab has the lead in this project for the development of algorithms for the reconstruction of molecular interaction networks from high-throughput multi-omics data. Emphasis will be placed on probabilistic graphical models and their use in causal inference. Moreover methods for the inference in larger, relational networks comprising cell-type information, patient and drug data should be developed. This will provide the formal basis of the virtual patient modelling efforts in the consortium.

The Postdoc will work on mathematical analysis and method development with the particular focus on utilizing recent high-dimensional single-cell data. Moreover, the student will work on algorithms for the incorporation and mining of structured and unstructured data related to cancer biology into a relational graph. The fellow will be given the opportunity to co-advise PhD students in the lab.

The fulfillment of the duties likewise enables the scientific qualifications of the candidate.

The Technische Universität Darmstadt provides the environment and support for publishing and presenting original research results at leading international conferences and in scientific journals.

Your profile:

  • completed Ph.D. studies in Statistics, Mathematics, Computer Science, Electrical Engineering or Physics
  • ideally, experience in the domain of bioinformatics, especially analysis of high-throughput data
  • a good publication record from Ph.D. studies
  • appreciation for interdisciplinary work and proactive drive to collaborate in a team


Your application must include

  • a cover letter explaining succinctly why you are interested in this position and why you believe you are the right candidate
  • a CV
  • contact details of at least two references (academic advisors) of yours

The Technische Universität Darmstadt intends to increase the number of female employees and encourages female candidates to apply. In case of equal qualifications applicants with a degree of disability of at least 50 or equal will be given preference. Wages and salaries are according to the collective agreements on salary scales, which apply to the Technische Universität Darmstadt (TV-TU Darmstadt). Part-time employment is generally possible.


Prof. Heinz Koeppl, Rundeturmstrasse 12, 64283 Darmstadt, heinz.koeppl@bcs.tu-darmstadt.de

Please send your application, incl. the above mentionned documents, as one single PDF file to: office@bcs.tu-darmstadt.de indicating the application code number within the subject line. Incomplete applications and applications in different file formats will be discarded.

Code No. 484

Published on

September 28, 2020

Application deadline

October 30, 2020