Research Assistant - salary grade E13 TV-L Berliner Hochschulen - For qualification

Research at the intersection of probabilistic machine learning, differential equations and Computational Neuroscience; characterization and modelling of numerical optimizations as dynamical systems through stochastic differential equations; system identification with deep neural networks, in particular with hybrid models such as Universal Differential Equations (UDE), Physics Informed Neural Networks (PINN), Hamiltonian Neural Networks (HNN) and Neural ODEs; software implementation of machine learning methods; teaching duties. opportunity for a doctoral degree.

• Successfully completed university degree (Master, Diplom or equivalent) in Computer Science, Physics, Engineering or Applied Mathematics
• Profound knowledge especially in probabilistic machine learning, as well as control engineering and dynamics of optimization methods, and the numerics of differential equations
• Practical experience in the development and application of machine learning algorithms, as well as parallel computing on GPUs.
• Solid programming skills, especially experience with ML and auto differentiation packages (JAX, PyTorch, SciML) and linear algebra libraries (Julia, Numpy, BLAS etc.)
• The ability to teach in German and/or in English is required; willingness to acquire the respective missing language skills

Desirable:

• Practical experience in the field of computational neuroscience

Please send your written application, quoting the reference number, with the usual application documents to Technische Universität Berlin - Die Präsidentin - Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Maschinelles Lernen, Prof. Dr. Klaus-Robert Müller, Sekr. MAR 4-1, Marchstr. 23, 10587 Berlin* or by e-mail (one PDF file, max. 5 MB) to: jobs@bifold.berlin.

The application documents will not be returned. Please only submit copies.

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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.