Research Associate (PhD/Postdoctoral Researcher) position for computer-based experiments to decipher the transcriptional program responding to stress in plants

In the Computational Biology research area, gene regulatory networks are generated using machine learning methods, and the resulting hypotheses are tested in the laboratory. This research project develops gene regulatory networks using machine learning methods in collaboration with experimental research groups in the USA and the UK. The complex regulatory program in plants responding to abiotic stress is deciphered from bulk RNA seq and single-cell ATAC seq data. A variety of machine learning methods are employed, with a particular focus on the explainability of the generated models.
The successful candidate will conduct computer-based experiments to decipher the transcriptional program responding to stress in plants. The results will be analyzed and discussed in close collaboration with the research partners.  

Your tasks

• Research tasks (90%):
  • Application of machine learning methods to create gene regulatory networks, including pre- and post-processing and the extraction of relevant features for prediction.
  • Comparative analyses in genomes and subgenomes
• Teaching duties (5%):
  • Participation in teaching events of the working group
• Other tasks (5%):
  • organizational participation in the work area

The position is conducive to academic qualification, and opportunities for further academic (or even professional) development are provided. Pursuing a doctorate while in the position is possible.

our range

• Remuneration according to E13 TV-L
• limited to 3 years (§ 2 para. 1 WissZeitVG; in accordance with the provisions of the WissZeitVG and the agreement on good employment conditions, a different contract duration may apply in individual cases)
• Full-time

• internal and external training opportunities
• A wide range of health, counseling and prevention services
• Reconciling family and career
• flexible working hours
• 30 days of vacation with a 5-day work week and additional days off on December 24th and 31st.
• good transport links
• Occupational supplementary pension scheme (VBL)
• collegial cooperation
• open and pleasant working atmosphere
• exciting and varied tasks

Your profile

That’s what we expect

• Completed relevant academic university degree (e.g. Master’s or equivalent) in biology, computer science or related subjects.
• Completed relevant doctorate (if employed as a postdoc)
• Experience in the application of machine learning methods documented by relevant publications or theses
• advanced knowledge of Python
• good English skills, both spoken and written
• independent, responsible and dedicated work
• strong organizational and coordination skills
• cooperative and team-oriented work style

That’s what we want.

• Experience in the analysis of biological data
• Experience in analyzing data from plants
• Experience in the creation of scientific publications 

Interested?

We look forward to receiving your application. Please preferably use our online form, which you can access via the “APPLY NOW” button below.

Application deadline: June 11, 2026