Offer 49 out of 86 from 13/10/21, 09:01


Tech­ni­sche Uni­ver­sität Ber­lin - Faculty IV - Institute of Software Engineering and Theoretical Computer Science - FG Machine Learning

Research Assistant - salary grade E13 TV-L Berliner Hochschulen

under the reserve that funds are granted; part-time employment may be possible

The Berlin Institute for the Foundations of Learning and Data (BIFOLD) of the TU Berlin is looking for a research assistant for an agility sub-project (AP) of the BZML. The AP is carried out in the "AI4Science " group of Prof. Dr. Frank Noé, at the Freie Universität Berlin (FU). The Noé group develops machine learning methods for the sciences, especially deep learning algorithms for the solution of fundamental problems in quantum mechanics and statistical mechanics of molecules.

Working field:

Research in the field of machine learning; development of new neural architectures for molecular interactions; equivariant learning structures; generative methods; software implementation of machine learning algorithms


  • Successfully completed university degree (Master, Diplom or equivalent) in Computer Science, Physics, Mathematics, Chemistry or similar is required.
  • Experience in the modeling and simulation of molecules, quantum mechanics and/or statistical mechanics are desirable
  • Extensive experience in the field of statistical methods and machine learning; prior experience with deep learning, multi-task learning and explainable AI is desired
  • Experience in training deep neural networks and are familiar with various network architectures (ConvNets, LSTMs, ResNets, Transformers etc.).
  • Very good programming skills in Python, NumPy / SciPy, PyTorch / TensorFlow are essential
  • Very good language skills in English and German required
  • Publication record in peer reviewed journals or workshops is desirable

How to apply:

Please send your application with the reference number and the usual documents (one file max. 5 MB) only by email to Prof. Dr. Klaus-Robert Müller at

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guaranty for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: or quick access 214041.

To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities.

Tech­ni­sche Uni­ver­si­tät Ber­lin - Der Prä­si­dent -, Fakul­tät IV, Insti­tut für Soft­ware­tech­nik und Theo­re­ti­sche Infor­ma­tik, FG Maschinelles Lernen, Prof. Dr. Klaus-Robert Müller, Sekr. MAR 4-1, Marchstr. 23, 10587 Ber­lin