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environment. Development of models to diagnose and predict battery performance and ageing. Participation in national and international research projects related with energy storage and its integration in
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projects on our Epic electronic health record platform. You will focus on integrating AI and predictive models into the Epic platform, enacting and facilitating standardized intake, design, and
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significant computational resources for centralized processing. Second, the existing centralized, terrestrial-based control infrastructure cannot scale with the increasing number of airborne sensors due
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approach. Fundamental research focuses on induced pluripotent stem cell (iPSC)-derived neuronal models to elucidate the molecular and cellular alterations contributing to neurodegeneration in familial and
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of hydrological connectivity of soil moisture using gridded soil moisture data sets and data-driven approaches (e.g., complex network methods) Develop models to predict gatekeeper locations and their relationship
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contribute to a major research project to improve our understanding of macroplastic pollution in coastal seas. Working at the intersection of numerical modelling and observations, you will develop simulations
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interest in social science applications, and with strong competence in statistics and machine learning. The successful candidate will develop predictive models using machine learning and work alongside other
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. Oversees the delivery and operating model for UFA’s data management and reporting function–including roadmaps, Jira/ServiceNow workflows, release/change management–ensuring predictable, transparent, and
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career-promoting work can be discussed and agreed Required selection criteria You must have strong competence in artificial intelligence, signal processing, modelling, instrumentation, or control
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neuroimaging data constrained by patient's structural connectivity and tractography • Using the results of the TVB model fits to stratify patients and predict disease progression • Organizing and unifying