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. The Postdoctoral Associate will work under the direction of the Principal Investigator in building a first-of-its-kind Software as a Medical Device (SaMD) that predicts, detects, and manages SSIs by fusing RGB
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uncertainty associated with high renewable penetration in a more systematic and effective way. Specific responsibilities may include: • Developing models (mathematical + software) of existing grid
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, and Michigan, and also link to other worldwide members of the tskit community. You will hold or be close to completion of a relevant PhD/DPhil in a quantitative subject (e.g. statistics, mathematics
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collaborators. Qualifications Applicants must hold a PhD degree in electrical/electronics engineering, telecommunications or related field. Other requirements include Expertise in several areas among
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the Universities of Edinburgh, Oxford, and Michigan, and also link to other worldwide members of the tskit community. You will hold or be close to completion of a relevant PhD/DPhil in a quantitative subject (e.g
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projects in artificial intelligence, materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Recently completed PhD within the last 0-5 years in computer science
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Master's and PhD students. Candidates will be responsible for creating a collaborative work environment within and outside QGG that integrates novel innovative research programs towards the green transition
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wearable sensors for resting breathing data collection. They will also ascertain whether the quality of home monitored data is suitable for SPAR analysis (in house software). Key responsibilities: Optimise
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readout. o Integration of optical tweezers, cavity QED systems, or quantum sensing technologies. · Technical Development: Innovate in vacuum systems, laser stabilization, and real-time control software
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fundamental research, we create widely used open-source software including autodE, cgbind/C3, and mlp-train. Our recent advances in Machine Learning Interatomic Potentials (MLIPs) form the foundation of our ERC