University of Tübingen
Tübingen, Germany
The position
The position is available within a multidisciplinary effort to develop new active substances against resistant bacteria in the project KI-gestützte Erschließung ribosomaler Naturstoffe: Ein Hochdurchsatzansatz zur Entdeckung antimikrobieller Wirkstoffe (KERN).
As a researcher, you will be welcomed at Pfeifer Lab and a vibrant campus environment in charming Tübingen. We have extensive knowledge at the interface between statistical machine learning, digital medicine, and computational biology, and plenty of collaboration opportunities beyond international borders.
Your Responsibilities
* develop a new generative AI approach for finding active substances against bacteria
* collaborate closely with colleagues from mass spectrometry, infectiology and machine learning
* present findings in peer-reviewed publications and international conferences
Your Profile
* a Ph.D. or equivalent degree in Machine Learning, Bioinformatics, Medical Informatics, Computer Science, Mathematics, or a related discipline
* strong programming/scripting skills (Python, R, C++, Java) and knowledge of ML frameworks (PyTorch, etc.)
* a competitive track record of scientific publications in machine learning, ideally for generative AI methods like diffusion models
* experience in Data Science and Machine Learning
* experience in the analysis of high-throughput data (multi-omics)
* experience with Vibe Coding is a plus
* a keen interest in interdisciplinary teamwork
* proficiency in English