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Field
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development (R&D) of advanced machine learning (ML) models like Transformers, Vision Transformers, Large Language Models (LLMs) and other advanced deep learning models for vision-based applications. The focus
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in-orbit servicing while exploring water extraction for a circular space economy. SpaceR is developing an RL algorithm for satellite rendezvous, docking, and liquid transfer, with tests conducted in
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through the Stanford Impact Labs Postdoctoral Fellowship Program (link is external) with Profs. Irene Lo, Itai Ashlagi, and the Stanford Impact Lab on Equitable Access to Education Postdoctoral Fellow
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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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structure, and of the force and tidal field that has been shaping the cosmic web. The basic detection algorithms to infer the overall structure of the cosmic web are the various versions of the scale-space
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algorithms, and decision-support tool development. Responsibilities will include programming, analysing and interpreting data, and contributing to innovative solutions that support maritime decarbonisation
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administered by the College of Natural Science and the College of Engineering, is one of the newest units at MSU. Founded in 2015, CMSE recognizes computation as the “triple junction” of algorithm development
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. Assess the build quality of parts generated through control model algorithms. Validate that methodologies developed are transferrable between different LPBF platforms through evaluation of parts generated
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models and numerical tools for accurately pricing such a real option. This project aim at filling this gap by developing novel mathematical models for pricing options of demand decrease, demand increase
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. The focus will be on deriving efficient algorithms with provable statistical guarantees, using tools from: high-dimensional statistics, optimization, probability theory, approximation theory etc