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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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] Subject Areas: Applied Mathematics, numerical methods, simulation and modelling Appl Deadline: 2025/05/31 11:59PM (accepting applications posted 2025/02/13) Position Description: Position Description
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Max Planck Institute for Plasma Physics (Greifswald), Greifswald | Greifswald, Mecklenburg Vorpommern | Germany | 2 months ago
-Institute for Plasma Physics in Greifswald offers within the division Stellarator Reactor Studies a PostDoc-position for a Physicist or Engineer (m/f/d) for the development of computational models
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the area of analytical aeroacoustics. The position is concerned primarily with the sound of unsteady vortex flows and their interactions with edges. The position requires a PhD in engineering or a
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. Successful applicants must have a PhD in a field related to survey methods techniques and transport demand modelling and demonstrated experience with state choice experiments, discrete choice models, virtual
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) assess future changes in these patterns under different global warming scenarios. Requirements: The successful applicant should hold a MSc or PhD degree in physics, mathematics/statistics, climate science
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Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work
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predictive control, and/or reinforcement learning. PhD (or soon to be completed) in engineering, applied mathematics, or computer science, with an ability to start in mid-late 2025 a research track record
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in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any