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Field
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on NLR’s HPC Collaborate with NLR researchers to assess tradeoffs between model detail and computational time Process and visualize results to inform algorithmic design Author, present and assist in
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research project). Experience with large datasets and statistical analyses (e.g., regression models) in R, STATA, or similar software is desirable. We particularly welcome applicants interested in
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, subject to an opinion issued by the respective supervisor(s). The report models, performance evaluation criteria, and the grant contract model are those approved under the University of Coimbra's Research
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supervisor(s). The report models, performance evaluation criteria, and the grant contract model are those approved under the University of Coimbra's Research Grant Regulations. Where to apply Website https
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are developed that prioritize interpretability and reduce data dependency by imposing desirable constraints on model behavior. We will divide our work into three thrusts: Thrust A: A first major objective will be
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, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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on model behavior. We will divide our work into three thrusts: Thrust A: A first major objective will be to augment classical spike train analysis methods particularly those developed by Prof. Grün and
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the field of quantitative marine science, particularly stock assessment modelling or ecosystem modelling. We encourage you to apply if you have a major or minor in mathematics, statistics, computing