Re­se­arch Po­si­ti­on (m / f / d) Ge­no­me Data Sci­ence

The Genome Data Science lab at the Faculty of Technology is headed by Prof. Dr. Alexander Schönhuth, who has an adjunct affiliation with the Center for Biotechnology (CeBiTec). Our research is centered on the development of computational methods and models that deal with machine learning / data science, data structures, algorithms and statistical models that serve the purposes to arrange, analyze and exploit the rapidly amassing genome data. Thereby, we cover a broad range of algorithms, software and protocols, from primary sequence analysis on the one end to sophisticated algorithms addressing involved questions in genetics, genomics and diseases on the end of high-impact applications.

Education provided by our lab focuses on combinatorial / statistical algorithms and models for the efficient analysis of genome sequencing data, the design of appropriate data structures for putting large amounts of genomes into mutual context (computational pan-genomics), and the design of machine learning (in particular deep learning) architectures and protocols that enable to exploit the rapidly accumulating genome data. While real life impact, for example in terms of truly promoting our understanding about diseases is very important, we put a clear emphasis on the creativeness and the pleasure when designing algorithms, data structures and network architectures that arises in our daily work. Your Tasks

research (75 %) in the following fields : metric learning for embedding large genome sequencing data

applying deep learning-based generative techniques (e. g., diffusion, flow matching) to generate genome data

applying mathematically oriented artificial intelligence techniques

performing attention- and state-space model-based methods for processing biomedical data

• teaching and teaching supporting tasks to the extent of 4 LVS (25 %)

Employment is conducive to academic qualification and provides the opportunity for further academic development. We offer

Your Profile We expect

Preferred experience and skills

Application Procedure

We are looking forward to receiving your application. To apply, please preferably use our online form via the application button below.

application deadline : Contact

Prof. Dr. Alexander Schönhuth

Postal Address

Universität Bielefeld

Technische Fakultät

Prof. Dr. Alexander Schönhuth

Postfach 10 01 31

33501 Bielefeld