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

Responsibilities

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. 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.

• 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

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

• salary according to Remuneration level 13 TV-L
• fixed-term (3 years, contract extension for 1 or 2 years possible)
• fulltime

Benefits

• internal and external training opportunities
• variety of health, consulting and prevention services
• reconcilability of family and work
• flexible working hours
• supplementary company pension
• collegial working environment
• open and pleasant working atmosphere
• exciting, varied tasks
• modern work environment with digital processes
• various offers (canteen, cafeteria, restaurants, Uni-Shop, ATM, etc.)

Qualifications

• completed scientific university degree (e.g., Master's degree) in a related subject area
• very good programming skills
• experience and sound knowledge of AI
• ability to work in a team
• cooperative and team-oriented way of working
• strong communication skills
• independent, self‑reliant and committed way of working
• strong organisational and coordination skills
• strong presentation and moderation skills

Preferred

• good written and spoken English 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

Equal‑Opportunity Statement

The university has received a number of awards for its achievements as an equal‑opportunity employer and has been recognized as a family‑friendly university. The university welcomes applications from women. This is particularly true with regard to both academic and technical posts as well as positions in information technology as well as the skilled crafts and trades. Applications are handled according to the provisions of the state statutes on equal opportunity. Applications from suitably qualified handicapped and severely handicapped persons are explicitly encouraged. At Bielefeld University on request positions can be carried out with reduced working hours as long as this does not conflict with official needs.