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.
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 firstname.lastname@example.org.
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: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/ 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