172 parallel-computing-numerical-methods positions at Technical University of Munich in Germany
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
of AI. The ideal candidates will have a background in computer science, statistics, mathematics, or related fields, as well as an interest in social science research methods and theories. The PhD
-
and satellite-based remote sensing data using High-Performance Computing at LRZ Publication of the results in scientific journals Assistance in teaching REQUIREMENTS: An above-average degree in
-
and Master’s students in Informatics and Data Science. Supervise Bachelor’s and Master’s theses. We Offer Practice-oriented research projects with leading academic and industry partners (like Google
-
very good Master’s degree in Computer Science, Medical Informatics, Business Informatics or a related field. Practical experience as a full-stack developer for cloud-native and/or on-premise applications
-
(ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together
-
mobility systems through practical and laboratory tests as well as sophisticated simulations. We not only publish research results gained at numerous conferences and in journals, but also make our software
-
Engineering, Computer Engineering, Computer Science, or a closely related field Strong background in robotics fundamentals: kinematics, dynamics, control, planning Proficiency in programming (C++, Python), and
-
academic supervision from Prof. Henkel. You will participate in the doctoral program of the TUM School of Management; after about a year, there is the possibility to apply for the School’s Academic Train-ing
-
PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
control of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human
-
develop methods and software tools that aid the design of microfluidic devices (also known as Labs-on-a-Chip). While these devices are mainly designed manually thus far, we investigate methods