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materials science. Ability and interest to work in a highly collaborative, interdisciplinary research environment. Preferred Qualifications Experience with graph neural networks, equivariant models
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materials research in collaboration with industry leaders. Combine chemistry, mechanics, and computation in a multidisciplinary team. Access cutting-edge experimental and modeling facilities. Contribute
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SPECIFICS Join a Dynamic Team Focused on Foundation AI modeling and Physics-Informed Machine Learning as a Postdoctoral Researcher at The Pennsylvania State University. The Pennsylvania State University is
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hope for cancer patients and their families and play a critical role in strengthening the fabric of our communities by gaining and protecting their trust and providing access to the outstanding oncology
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, dendrite growth, side reactions, delamination, and related behavior in hard and soft materials. A strong emphasis will be placed on the integration of AI methods and agentic workflows into model development
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for malaria and other neglected tropical diseases. This will be done by developing mathematical and statistical models, to describe the time course of drug concentrations and effect. You will work closely with
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collide, condense and evaporate. Guided by the results from the field campaigns, a new Microphysics Informed Large-Eddy-Simulation (MiLES) model will be developed. The tested and verified MiLES will be
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Job related to staff position within a Research Infrastructure? No Offer Description Work group: Hybrid Material Systems Area of research: Scientific / postdoctoral posts Job description: Reference
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Carilion (VTC). About the Lab: The lab integrates state-of-the-art neural recording technologies, complex cognitive tasks, and computational models to investigate the neural basis of flexible cognition. From
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, which remains a major global health challenge and an important cause of liver related morbidity and mortality. Our laboratory has a strong history of developing innovative human models of viral infection