61 parallel-computing-numerical-methods-"Prof" uni jobs at Technical University of Munich in Germany
Sort by
Refine Your Search
-
, is essential. A very good Master’s degree in Biology or a closely related discipline is required. The project will be carried out in the group of Prof. Dr. Ralph Hückelhoven under co-supervision by Dr
-
(WNVI) framework and aims to advance its capabilities in the following directions: • Scalability: Extending methods to high-dimensional and three-dimensional elastography problems using neural operator
-
technical alignment in the three use cases. The PhD candidate will be able to carry out a dissertation project within the framework of LLMs governance supervised by Prof. Dr. Urs Gasser (TUM). Eligibility
-
(WNVI) framework and aims to advance its capabilities in the following directions: • Scalability: Extending methods to high-dimensional and three-dimensional elastography problems using neural operator
-
-cell data has its own statistical and computational challenges, and standard tools often cannot be applied. The purpose of the position and goal of the project is to develop and apply bioinformatic tools
-
/d) in Energy Informatics, specifically for a DFG project in wind power forecasting using machine learning. You are passionate about applying cutting-edge information technology to solve the energy and
-
scientific work on design automation for quantum computers and develop methods and software tools dedicated to the design and realization of quantum algorithms/circuits. One of the main challenges in
-
methods (such as Machine Learning, Metric Learning, Reinforcement Learning, Graph Representation Learning, Generative Models, Domain Adaptation, etc.) for Design Automation applications. To this end, we
-
• Conduct statistical consultation for Helmholtz scientists and industry partners • Evaluate and apply novel statistical methods in the context of applied research • Write statistical reports on experimental
-
Computational Molecular Medicine, led by Prof Julien Gagneur, develops computational approaches to study the genetic basis of gene regulation and its implication in diseases. Applications of our work range from