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Field
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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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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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We’re looking for a motivated PhD student with a Master’s in Robotics, Control Theory, Applied Math, or Mechanical Engineering eager to work on model-based control of soft robots Job description We
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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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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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offered in this context, with the objective of modelling, coding, and field-validating a new mechanistic analysis tool for pavements containing fungal-bound granular layers. The research will focus on urban
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address: Dr Fahad Panolan: f.panolan@leeds.ac.uk Project summary The Algorithms group at the University of Leeds (UK) is offering a fully funded 3.5-year PhD studentship on Parameterized Complexity and
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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