169 parallel-computing-numerical-methods positions at Technical University of Munich in Germany
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
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
-
). 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
-
efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a sustainable future. These
-
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
-
Engineering, Operations Research, Civil Engineering, Computer Science, Data Science or a related field, from a university/department with a strong international research reputation Strong mathematical and
-
mobility, user demands, wireless system deployment) as well as the digital world (such as networking, memory, computational resources for different applications). Information about the physical and digital
-
Learning in Earth Observation (ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University
-
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
-
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
-
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