PhD/PostDoc position in AI and molecular design

[Heinz Koeppl]

The Self-Organizing Systems Lab at TU Darmstadt, Germany is seeking to fill a 

PhD or PostDoc position in the domain of machine learning for synthetic biology. 

The aim of the research is to develop new domain specific machine learning methods for complex sequence-to-function mappings (for DNA, RNA and proteins) and for uncertainty quantification in the context of Bayesian optimization. We will investigate different designs for foundation models for molecular structures and look into adapted autoregressive architectures for molecular sequences. The group hosts its own biochemical laboratory and can hence generate domain specific and well-controlled training data on its own. 

We look for a computer scientist, mathematician, physicist or engineer eager to engage in this interdisciplinary research. Ideally the candidate should have a prior exposure to molecular biology or at least a strong drive to learn the necessary biology. Good programming skills is a must. 

Interested candidates should submit a short motivation letter, a CV, transcripts of records and contact details of at least two academic references in a single PDF-file to: off...@bcs.tu-darmstadt.de

Application Deadline: August 22, 2025