Research fellow (m/f/d) in the field of Machine learning and Biomedicine

Overview

Prof. Ohler's research group focuses on decoding and designing gene regulatory networks through high-throughput genomics and applied machine learning. The successful candidate will contribute to our focus on the application of explainable AI for decoding and designing gene regulatory sequences.

Responsibilities

• scientific services in research within the project of the DFG-funded AI research group "Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (DeSBi)"
• development of deep neural networks and machine learning algorithms for the analysis of extensive omics data
• adaptation and application of methods from explainable artificial intelligence to understand gene regulation at different levels of abstraction
• adaptation and application of foundation models for omics data
• development and documentation of scalable benchmarks and/or pipelines for training interpretable models
• application and validation of the approaches on (single-cell) data from the laboratory (Max Delbrück Centrum Berlin) and from cooperation partners
• presentation of research results at internal and external meetings and conferences and publication in scientific journals

Qualifications

• completed scientific university degree and, if applicable, PhD: either in computer science, data science, bioinformatics, or a related field with a focus on machine learning; or in other areas of natural sciences with extensive experience in statistical methods and machine learning for the analysis of biomedical data
• excellent programming skills (e.g., in Python, NumPy/SciPy, PyTorch/TensorFlow)
• experience working with cluster/GPU computing resources is desirable
• excellent verbal and written communication skills and the ability to work effectively in a collaborative team environment
• strong problem-solving and analytical skills as well as the ability to think creatively
• very good command of written and spoken English (at least B2)

How to apply

Please send your application (including a cover letter, CV, relevant certificates, transcripts and contact information for at least two references), referencing the job id DR/006/26 to Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Biology, Prof. Dr. Uwe Ohler, (Address: Hannoversche Str. 28, 10115 Berlin), Unter den Linden 6, 10099 Berlin, or preferably via email as a PDF file.

The position is scheduled to be filled on March 15, 2026.

Additional information

The Humboldt-Universität zu Berlin is seeking to increase the proportion of women in research and teaching, and specifically encourages qualified female scholars to apply. Severely disabled applicants with equivalent qualifications will be given preferential consideration. People with an immigration history are specifically encouraged to apply. Since we will not return your documents, please submit copies in the application only.

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