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Field
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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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. 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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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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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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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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or game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of applicants
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in chemistry and biology, approaches for extracting relevant information from foundation models, and/or methods for adaptive experimental design such as active learning or Bayesian optimization
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machine learning is an advantage but is not required. Experience with the design and implementation of survey-experiments is an advantage but not a requirement. Alongside developing their own research ideas
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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
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, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of applicants primarily hinges on their documented academic qualifications and the