Research tasks in the field of machine learning, i.e. development of deep neural networks and application thereof to complex, heterogeneous data. Development of robust and interpretable models incorporating prior knowledge from the application domains. Advancement of methods to interpret and explain the predictions of deep neural networks. Supervision of Bachelor/Master/PhD students.
Successfully completed university degree (Master, Diplom or equivalent) und doctoral degree in computer science, mathematics or physics. Several years of experience as scientific research assistant in the field of machine learning. Extensive and deepened knowledge on: methods and theory of machine learning, deep neural networks, explanation methods, interpretable models, application of machine learning methods on real-world high-dimensional data: regression, classification, and clustering as well as their empirical evaluation.
Very good programming skills and expertise in using mathematical software and simulation environments such as Python together with machine learning/neural networks such as PyTorch or Tensorflow. Experiences in interdisciplinary research as well as publications in machine learning journals and/or conferences are desirable. Very good command of German and English is required.
How to apply:
Please send your written application with the reference number and the usual documents to Technische Universität Berlin - Der Präsident - Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Maschinelles Lernen, Prof. Dr. Müller, Sekr. MAR 4-1, Marchstr. 23, 10587 Berlin or by e-mail to firstname.lastname@example.org.
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.
Please send copies only. Original documents will not be returned.
Technische Universität Berlin - Der Präsident - Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Maschinelles Lernen, Prof. Dr. Müller, Sekr. MAR 4-1, Marchstr. 23, 10587 Berlin