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, we are seeking a university assistant to develop advanced machine learning methods for improving the simulation and optimization of distributed systems, for instance by specializing neural ODEs and
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the simulation and optimization of distributed systems, for instance by specializing neural ODEs and their training routines. This research will address challenges driven by the energy transition, which is
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, develop, and troubleshoot high-end NMR spectrometers (400–700 MHz, solution- and solid-state NMR, EPR, Prodigy and He-Cryo units), ensuring optimal performance and reliability. Method development: Develop
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(400–700 MHz, solution- and solid-state NMR, EPR, Prodigy and He-Cryo units), ensuring optimal performance and reliability. Method development: Develop and optimize pulse programs and parameter sets
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, and high-performance computing for biotechnological applications. The project aims to develop computational tools for bioprocess optimization, combining modeling, simulation, and data-driven methods
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Learning, Neural Networks, Optimization, Applied Harmonic Analysis, Inverse Problems, Quantum Information, and other relevant areas. Additionally, the position will be associated with the Research Network
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Computing Cloud Computing Performance Analysis and Optimization Communication Technologies for Supercomputers Workload Management and Scheduling Optimization of LLM Training and Inference Our working language
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for applications in chemical biology and medicinal chemistry. Synthetic research work will take place in close coordination with experts in molecular biology and cell biology to enable the optimal design of
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expertise in fields that are of great important for the Tenure Track position, such as Machine Learning, Neural Networks, Optimization, Applied Harmonic Analysis, Inverse Problems, Quantum Information, and
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. The research focus of our group is on parallel computing, supercomputing, and performance tuning and optimization of advanced applications. Our team currently consists of 10 scientific and 3 administrative