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knowledge-grounded reasoning with flexible machine learning Tools that reduce manual burden while preserving traceability and clinical interpretability This position offers the opportunity to publish novel
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-machine interfaces. Experience with AI methods such as generative models, reinforcement learning, online/adaptive learning, or uncertainty quantification. Research experience in rehabilitation engineering
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with 5+ years experience OR Master's degree with 2+ years experience in Biomedical Engineering, Mechanical Engineering, Electrical / Electronic Engineering, Computer Engineering, HealthTech, MedTech
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to make the synthesis of model organism genomes (i.e. E. coli) more rapid and enable the synthesis of the genomes of non-model bacteria to broaden the scope of genome synthesis. The ability to routinely
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2. Modeling for Regulatory Science – Leveraging drug development and regulatory
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(kidney biopsy, serum, urine) for comprehensive biomarker profiling. Utilization of machine learning and image processing for advanced tissue analysis. The Herman B Wells Center for Pediatric Research
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and Distributed Systems Research Group (ND) with co-supervision from IFI’s Machine Learning section and the University of Inland Norway’s research group for User Perception and Engagement in XR
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research position under the supervision of Dr. Chris Smith Home | Chris Smith . The lab— in the Evolution, Ecology, and Behavior section—investigates machine learning approaches for spatial population
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. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations of reactor transients and quantify how surrogate uncertainties propagate
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, modeling machine learning, and scientific simulation Ability to work well in an interdisciplinary environment, and to collaborate with experimentalists Strong oral and written communication, data