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Department of Chemical and Biological Engineering at Princeton University. The position is in the broad area of renewable energy systems synthesis, analysis, and optimization. The goal of the project is to
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the date of hiring. 4. Work plan: 4.1. The main tasks to be performed under the grant will be: a) Optimization of pharmacodynamic assays for in vitro and in vivo testing. b) Conducting pharmacodynamic
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expect an excellent publication record in areas such as automated planning, machine learning, logic or combinatorial optimization. Furthermore, candidates should have very good programming and
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cancer, in a single location in Utrecht. Our institute aims to provide the highest level of care for all children with cancer, with optimal quality of life. The center brings together the best possible
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 hours ago
professionalism, enhance learning, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our
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in Statistial models for optimizing the chemical process Skills in elemental & structural analysis using various existing techniques. Knowledge in advanced structural characterizations will be valued
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, Quantum Biomedicine, Quantum Machine Learning, Quantum Optimization, etc. The positions are normally for one year and are renewable for a second and a third year, subjected to satisfactory research
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optimization of community PV systems, e-mobility, and edge data center integration at the Swiss pilot site hosted at Empa’s NEST demonstrator. The role involves coordinating the deployment and validation
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for application in biocatalysis. Enzyme kinetic analysis. Development and optimization of multi-enzyme cascade reactions. Disseminating project results through scientific publications and conference presentations
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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a