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highly motivated and technically proficient Research Fellow in Control and Embedded Systems Engineering to support the development and deployment of intelligent, safety-enhanced BMS technologies within a
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decision making, while you will be capable to apply machine learning and computational algorithms of social choice. This post is associated with following projects: Embedding EDI in the Distribution
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: • PhD (or strong industrial experience and a Master’s degree) in Control Engineering, Power Electronics, Embedded Systems, or closely related disciplines. • Proven experience in the design and
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Queen’s Communities and Place (QCAP) is an AHSS Faculty flagship research initiative based in the School of Social Sciences, Education and Social Work. It launched in November 2021, and supports
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annum dependent on qualifications and experience, in line with current pay protection and transitional arrangements in the NHS. This is a full time, fixed term position for 12 months. The Oxford
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continuation of PhD research. Prior to applying, discussions regarding the planned research proposal must be held with a University of Lincoln academic staff member who is willing to act as the Fellowship
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embedded AI systems. They will demonstrate a strong track record of high-quality research in machine learning/AI and/or embedded systems, evidenced by publications in leading conferences and journals
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Queen’s Communities and Place (QCAP) is an AHSS Faculty flagship research initiative based in the School of Social Sciences, Education and Social Work. It launched in November 2021, and supports
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, identify targetable vulnerabilities, and contribute to next-generation precision medicine approaches. With joint supervision from leading professors and embedded in interdisciplinary world-class facilities
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the following areas is advantageous: Participation in Kaggle competitions, showcasing practical problem-solving and model development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded