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team. The position is embedded within a newly funded ERC Consolidator Grant, further supported by the SyNergy Cluster of Excellence and the newly established Collaborative Research Centre CRC 1744
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culture at NYUAD. Participate in cross-disciplinary projects at CITIES, connecting data systems to applications in urban science, planning, and decision support. Qualifications Required: PhD in
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Job Description Are you looking to grow your career in intelligent embedded systems and edge computing? Join the Embedded Systems Engineering (ESE) research section at DTU Compute , where your
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%). You will work on the extension of the DUNE-FEM package to support computations on GPU hardware with various types of Finite Element methods. This work is embedded in a research project considering
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on the effective integration of renewable energy, resource efficiency, and waste reduction. The candidate must hold a PhD in Urban or Rural Development, Civil Engineering or related domain. The candidate is expected
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required PhD in one of the following fields: electronics and embedded systems, telecommunications, industrial computing, electrical engineering or equivalent. Expertise in the design, prototyping and
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Telescope and WIYN telescope. Computing access is supplied by the Penn State Institute for Computational and Data Sciences . Education and Experience A PhD in Physics, Astronomy, or a closely related field is
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at each stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In
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. Background: You hold a PhD in Computer Science, Machine Learning, Electrical Engineering, Embedded Systems or related fields. Core Expertise: Strong expertise in Federated Learning and/or Continual Learning
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to apply for this position. Curriculum Vitae with a full list of publications, and two references with their contact details. A short description (150 – 250 words) of your PhD research and a copy of your PhD