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CORE A*/A conference paper. We invite applications for a postdoctoral position focused on the development of predictive models for clinical outcomes following Deep Brain Stimulation (DBS) in Parkinson’s
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, and clinical data. - Apply machine learning and foundational modeling to support predictive or exploratory analyses. - Collaborate with interdisciplinary teams to refine multi-modal pipelines
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have extensive knowledge on processes governing cross-shore transport and can use experimental data to develop predictive models. Experiences within numerical modelling of coastal processes is considered
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, aimed at revolutionizing the way osteoarthritis is understood, diagnosed and treated by developing multimodal patient-relevant endpoints, advanced predictive models, and next-generation clinical trial
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perturb sequencing to establish foundational models to predict the effects of potential drug candidates on cardiovascular diseases. By combining genome engineering, functional genomics, and tissue models
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the direction of the Principal Investigator in building a first-of-its-kind Software as a Medical Device (SaMD) that predicts, detects, and manages SSIs by fusing RGB + thermal wound images
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of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models. Develop multistate sequence design algorithm for rational design of RNA switches. Develop database
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are considered the largest source of uncertainty in climate predictions because it is complicated to accurately model the small-scale process (microphysics) inside clouds occurring in a range from meters to
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part of the international Refuge-Arctic project (https://www.refuge-arctic.ulaval.ca ) with links to the NASA FORTE project, whose overall objective is to better understand and predict the role played by
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attention to scientific rigor and interpretability Experience with XAI tools (SHAP, LIME, Integrated Gradients) to identify which features of the model are driving the predictions Clear written and verbal