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of models like CNN, RNN, Transformers with some work in classical machine learning with XGBDTs is expected. Relevant work can lead to co-author publications and contributions to grant proposals. Tentative
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the scientific supervision of Professor José Carlos Magalhães Duque da Fonseca. Grant duration: Initial duration of 3 months, with the predicted starting date in april 2026, on an exclusive basis eventually
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applicant will work with the ReXIl team, AIML, and 4DMedical to turn data into clinical impact. They will be responsible for developing algorithms for image analysis, creating predictive models for disease
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AI to predict safety outcomes for multiple targets and combination therapies Collaborate with research teams and data scientists to design data-driven strategies using machine learning/AI methods
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the Sustainability Institute at University College Cork. UCC invites applications for a Postdoctoral Researcher with strong expertise in fault detection, diagnostics (FDD), and preventative/predictive maintenance
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
to perform disease modeling and critical analytics in response to infectious disease outbreaks. Duties will include helping to implement predictive and analytic models of infectious disease using Python and R
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, product management work, and and leadership responsibilities • Familiarity with artificial intelligence and machine learning approaches, including predictive modeling and precision analytics applied
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
neurological disorders with adult and/or pediatric patients, and with predictive testing for variable onset disorders. They should be comfortable seeing patients independently and using a variety of practice
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kidney disease in adults: assessment and management. Clinical guideline [CG182]. Tangri N, Stephens LA, Griffith J et al A Predictive Model for Progression of Chronic Kidney Disease to Kidney Failure. JAMA
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or area related to that requested in the tender. Preferential factors: Prior experience in parametric analysis and simulation of building thermal performance, Life Cycle Assessment, prediction and