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optimization technologies are revolutionizing the way power grid is operated and planned. CEEESA is seeking talented and motivated researchers to enhance its capability in solving energy challenges using
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collaborative environment with projects and interactions spanning multiple labs within the group, across NIST and externally. Candidates should have a PhD in physics, electrical engineering, mechanical
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adaptive optimization during needle insertion, integrating live ultrasound imaging with GPU-accelerated dose calculation and optimization. The Postdoctoral Research Associate will join a multidisciplinary
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contribute to overall optimization minimizing CO2 emissions and overall cost.’ Qualification requirements Appointment as postdoc requires academic qualifications at PhD level. How to apply Your application
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. Role & Responsibilities: Design and optimize large-scale electrophysiological and behavioral experiments using next generation custom-built hardware and software platforms Develop and implement end
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thermoplastic feedstocks for FDM printing Programming of an existing hybrid FDM printing machine, including printing and milling devices Modelling and optimization of the debinding process Simulation-based design
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the research team in the area of Swarm Intelligence, Reinforcement Learning and Optimization Techniques. As a Postdoctoral researcher, you will: Lead cutting edge research in Swarm Intelligence and Machine
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, the generated data can be used to optimize mineral extraction processes from existing mines within a geometallurgical framework. The position will mostly focus on the development of measurement protocols and data
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-symmetry-handling-in… Requirements Specific Requirements Motivated researcher, with a PhD in integer programming, bilevel programming, mathematical optimization, or a comparable domain. Very good programming
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colleague? Apply now! Education • PhD in Computer Science, Telecommunications, or a closely related field. • Solid knowledge of mobile networks and 5G systems, with practical understanding of RAN optimization