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28 Aug 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Computer science Physics Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country United Kingdom Application Deadline 9 Sep 2025 - 00:00 (UTC) Type of Contract Other Job...
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Posting Title Researcher II/III: EMT Modeling, Simulation and Analysis for Large-Scale Power Systems . Location CO - Golden . Position Type Regular . Hours Per Week 40 . Working at NREL The National
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student will develop novel, generalized models of doping in semiconductors, based on the drift-diffusion framework of Fluxim’s simulation software Setfos. The PhD project involves the following
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excursions. The PhD student will work on analysing the reliability of paleomagnetic records, deriving uncertainty estimates, and building time-dependent models of the paleomagnetic field evolution using a
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integration of energy systems data and models and apply data science methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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the development of components using agent-based modeling techniques, reinforcement learning, and other explainable artificial intelligence modules for decision-making, situation assessment, and operational support
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Master’s in Robotics, Control Theory, Applied Math, or Mechanical Engineering eager to work on model-based control of soft robots Job description We are looking for a motivated PhD candidate to join the
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Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Estonia Application Deadline 24 Oct 2025 - 23:59 (Europe/Tallinn) Type of Contract Temporary
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, the PhD researcher will develop physiological-model-based artificial intelligence technologies to assess patients’ recovery process, detect or even predict the occurrence of clinical adverse events like