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on developing a new multi-disorder prediction approach that integrates different sources of information. You work with analytical model development, extensive simulation studies and analysis of existing large
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, particularly sialic acids, influence and suppress immune responses against peritoneal metastases; test in patient material and in vivo models whether sialic acid inhibition reactivates the immune system; analyze
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, enabling systematic and efficient exploration using modeling and simulation tools.For the full details please check: https://workingat.vu.nl/vacancies/phd-in-reconfigurable-spatial-accelerators
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» Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Netherlands Application Deadline 27 Feb 2026 - 12:30 (Europe/Amsterdam) Type of Contract To be defined Job Status
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or above). For more details please check the Graduate Schools Admission Requirements: https://www.tudelft.nl/onderwijs/opleidingen/phd/admission . TU Delft (Delft University of Technology) Delft University
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statistical models to predict treatment response; optimizing individualized rTMS targeting using neuronavigation and computational modeling; designing and conducting n-of-1 trials embedded in routine clinical
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involving Fluid Dynamics. Demonstrable affinity with studying the physics of the ocean and preferably with polar oceanography. Experience with numerical modelling. Excellent ability to communicate in both
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seeking for motivated candidates that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon models and
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muscles, bones, joints, and associated tissues, are the leading cause of disability worldwide. Musculoskeletal models hold great potential for prevention and development of new treatments, but current
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environments. The researcher will work on modelling relevant propagation effects, designing localization strategies robust to urban acoustics, and validating these techniques using state-of-the-art experimental