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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly
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include supervision of projects, teaching courses at bachelor's and master’s level, and examination as well as possible supervision of PhD students. Furthermore, you should contribute to the development
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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techniques for integrating such solutions into modern SDV middleware. Responsibilities: Conduct research in runtime analysis and reconfiguration of in-vehicle TSN networks. Develop algorithms and prototypes
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will develop in the position; it is expected that you have previous experience on each of them: Develop and implement CFD models to simulate the behavior of PRO systems. Apply ML algorithms to optimise
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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position to develop and apply emulators for Earth System Models (ESMs), with a particular focus on the role of the biological carbon pump in oceanic carbon cycling and climate feedbacks. The research will
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involves the use of quantum chemistry, machine learning, and genetic algorithms to search for new homogeneous chemical catalysts. Who are we looking for? We are looking for candidates within the field
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Job Description The Institute of Mechanical and Electrical Engineering invites applications for a 24-month scholarship as a postdoctoral researcher in development of topology optimisation methods