Department Artificial Intelligence in Biomedical Engineering

Biomedical Network Science Lab

https://bionets.tf.fau.de

• Regular promotion to the next level and increase in salary pursuant to the collective bargaining agreement for the public service of the German Länder (TV-L) or remuneration pursuant to the Bavarian Public Servants Remuneration Act (BayBesG) plus an additional annual bonus
• 30 days annual leave at five working days per week with additional free days on December 24 and 31
• Occupational pension scheme and asset accumulation savings scheme

• We are flexible regarding working hours and workplace.
• Although we are a computational lab, you can benefit from various ongoing collaborations with wet lab scientists.

We are launching a high-risk high-gain project in the field of computational epigenetics: Our aim is to develop computational methods to infer upstream regulators of DNA methylation from matched gene expression and DNA methylation data, using a combination ML, network-based modeling, and classical bioinformatics pipelines. If such upstream regulators exist at all is currently unclear, but if they do, they would constitute a new functional class of proteins that not only regulate a fundamental biological program but are also putative targets for novel therapies in diseases driven by aberrant DNA methylation. We are seeking a creative and highly independent postdoctoral researcher to lead the method development in this project.

• Ability to independently carry out creative, rigorous, and reproducible scientific work in the field of computational biology/ML for omics, as evidenced through publications in leading life sciences and/or ML journals or conference proceedings.
• Strong interest in epigenetics and willingness to engage in collaborations with wet lab scientists.
• PhD (completed or almost completed) in bioinformatics, machine learning, computer science, or a related field.
• Master's degree in computer science, bioinformatics, applied mathematics, or a related field.

Please provide the following documents with your application:

• Cover letter where (i) you explain why you are interested in the position and (ii) provide the full references of your two best publications (including links/DOIs), briefly describe them, and tell us why you are proud of them. Important: write this letter yourself, do not AI-generate it. Name this document "<your surname>_cover_letter.pdf".
• Your two best publications in one joint PDF if they are not available open-access. Name this document "<your surname>_best_papers.pdf". If your two best publications are both available open-access, this document can be omitted.
• CV including full list of publications and contact details for two referees. Name this document "<your surname>_cv.pdf".
• Transcripts and certificates for your Bachelor's degree, Master's degrees, and PhD degree (if already available). Name this document "<your surname>_certificates.pdf".