Research Associate- salary grade E 14 TV-L Berliner Hochschulen - for qualification

Development of Neural Networks, esp. of models for application to complex, structured data from quantum chemistry; development of scalable algorithms for data analysis of high-dimensional and rapidly growing data sets; application and development of novel methods e.g. in the areas of the inverse design of molecules and materials with deep neural networks or their application to the analysis of atomistic systems in quantum chemistry; opening up of new research directions. Teaching duties.

• Successfully completed university degree (Master, Diplom or equivalent) and PhD in Computer Science, Mathematics or Physics
• Several years of teaching & research experience, profound knowledge in the field of theory and practice of ML, esp. NN, DL, equivariant NN, generative models, as well as the application area of quantum chemistry
• Sound knowledge of Python as well as DL Bibs, such as PyTorch, JAX, or Tensorflow
• Excellent mathematical skills, esp. linear algebra, probability, group theory, differential geometry and statistics
• The ability to teach in German and/or in English is required; willingness to acquire the respective missing language skills

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

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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. Applications from people of all nationalities and with a migration background are very welcome.