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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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, or a closely related discipline with a strong academic record Genuine interest in data-driven and physics-based modeling, molecular simulations, and their application to bioprocesses and bioseparations
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link: https://www.ncbi.nlm.nih.gov/myncbi/nathan.lawson.1/bibliography/public/ Send related inquiries to: Nathan D. Lawson, Ph.D. Professor Department of Molecular, Cell, and Cancer Biology University
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investigate HIV-induced vascular dysfunction and neuroAIDS molecular mechanisms using in vitro and in vivo (animal models) approaches. Specifically, the person will utilize HIV mouse models and HIV-1 infected
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Postdoctoral researcher (M/F), synthesis of crystal phase heterostructures by Molecular Beam Epitaxy
optimize the growth of GaAs nanowires integrating crystal-phase heterostructures by molecular beam epitaxy (MBE). Contribute to scientific writing, presentation of results, and promotion of the project's
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, molecular biology, biochemistry, immunology, or related field, with a strong focus on murine myopathy models. Demonstrated experience in in vivo experimentation, including animal handling, dosing, tissue
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communication. They will implement cellular models and cellular/molecular biology approaches to link metabolic regulation with subcellular organization. The LPENS laboratory offers a unique interdisciplinary
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change. To apply, visit https://northeastern.wd1.myworkdayjobs.com/en-US/careers/job/Boston-MA-Main-Campus/Postdoctoral-Research-Associate--Translational-Muscle-Biology--Murine-Models-_R138320 Copyright
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. * Examine mechanisms of organ cross-talk between the heart, vasculature, and brain. * Utilize in vitro and in vivo models, including inflammatory and aging-related models. * Perform molecular
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understanding of electrolyte performance from molecular to device-relevant length scales. The main task for the doctoral candidate will be to develop and apply computational models to quantify and predict key