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employment with a maximum period of 3 years. The main responsibility of this position is to contribute to research projects focusing on modelling, optimization, control, and AI applications for smart
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optimization of new reactions and for high-throughput synthesis of libraries for biological screening. Additional responsibilities include creating policies and procedures for use of the center’s facilities by
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testing of model-free algorithms for real-time optimization of turbine operating conditions (e.g., yaw set points). Other projects may be assigned by the supervisor depending on skills and technical needs
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optimization, and working knowledge of machine learning (ML) algorithms Demonstrated exceptional problem-solving abilities, a passion for collaborative research, and a commitment to making a tangible real
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system through open-source modeling and collaborative research. The successful applicant will play a central role in developing and applying Tools for Energy Model Optimization and Analysis (Temoa
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research at the intersection of aerospace and artificial intelligence, developing cutting-edge techniques in machine learning, optimization, control, and estimation. Current research thrusts include
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optimization, intelligent runtime systems, code generation and transformation, HPC, parallel and distributed computing, compiler infrastructures, heterogeneous systems, and autonomous system optimization
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systems through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to
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catalysis and reactor system optimization for sustainable energy and chemical conversion. The research will explore the integration of electrochemical processes with enzymatic catalysis for the selective and
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-oriented problems involving optimization, artificial intelligence, workflow redesign, and stochastic assembly line balancing. The position will involve close collaboration with industry partners