Research Assistant (E13, IV-618/24)

Prof. Dr. Uwe Ohler (MDC) and Prof. Dr. Grégoire Montavon (BIFOLD) are looking for a research assistant in the field of machine learning and medicine for a BIFOLD Agility project focused on self-supervised learning on high-throughput biological data for decoding and designing gene regulatory circuits.

The Ohler lab focuses on decoding and designing gene regulatory circuits by means of high-throughput genomics and applied machine learning. The BIFOLD-JRG Montavon is developing new methods for explaining complex ML models with applications in medicine. The project includes the following aspects: (i) Develop generative machine learning models and algorithms for the analysis and integration of large-scale omics data. (ii) Implement and/or tune foundation models for -omics data. (iii) Adapt and utilize methods from explainable artificial intelligence to understand gene regulation. (iv) Develop and document scalable pipelines for reproducible analyses. (v) Apply and validate your approaches on (single-cell) data from our lab and our collaborators.

Tasks

You will (i) work in a collaboration of two groups at the Berlin Institute for the Foundations of Learning and Theory (BIFOLD) and the Max Delbruck Center for Molecular Medicine (MDC), (ii) work with an integrated team of experimental and computational scientists to apply cutting edge explainable AI to decipher gene regulation, (iii) collaborate with team members to integrate and interpret data from multiple sources, (iv) present research findings at internal and external meetings and conferences, (v) publish your findings in high-impact scientific journals, and (vi) contribute to grant applications or other funding applications to develop your own independent research interests. Teaching tasks.

Salary grade: TV-L 13, Berliner Hochschulen
Starting date: March 01, 2025 (limited for 3 years)
Closing date: December 13, 2024
Full job posting: IV-618/24