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objective prediction of biological aging, but also the improvement of age-related phenotypes such as cognitive decline, muscle weakness, bone density loss, and kidney dysfunction. Our research is particularly
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behavior of both engineering and natural systems and develop predictive tools for mechanical failure. Our team is highly interdisciplinary and international, bringing together researchers with backgrounds in
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Context: Controlling heat and particle fluxes on tokamak walls is a critical challenge for future tokamaks. Achieving burning plasmas near ignition while ensuring sufficient power distribution on divertor
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/2026 Group or Departmental Website: https://med.stanford.edu/supekar-lab.html(link is external) How to Submit Application Materials: Please email application materials as a single PDF to supekarlab
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, and unsafe conditions Maintain building security practices, including oversight of key control and access accountability Support audits, inspections, and required compliance documentation Financial
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research programme in fundamental AI, AI co-scientists, and applications in complex scientific domains such as RNA sequence-function modelling, structure prediction, and inverse design. Further information
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correlate the findings with prognostic parameters, refining the prognostic value of the Immunoscore for MuM in order to identify predictive biomarkers and refine TME-based therapies. Project aim: The aim
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to predict marine extremes for engineering and navigation purposes The PhD candidate is expected to develop an integrated framework that combines machine and deep learning methods with statistical and
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of artificial intelligence (AI) technology is increasingly infused in our everyday lives, AI's role in education (K-12, higher education and corporate) is less clear. Some are predicting that AI will enhance
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research, digital health solutions, and the development of AI-based predictive models using large-scale clinical datasets. This position is particularly suited to a clinician-scientist with a strong