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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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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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. * 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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– Molecular-Scale Modelling This PhD position focuses on molecular-scale computational modelling of polymer-hybrid anion-exchange membranes. The project involves DFT, molecular dynamics, and Monte Carlo
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disease. The molecular mechanisms driving the individual endotypes of severe asthma have not been fully characterized, and in vitro model to develop endotype-specific therapeutic interventions or biomarkers
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
Department of Molecular Medicine at SDU is looking for applicants for a PhD scholarship within the field of biomarker and therapeutic target investigations in biliary atresia. We are looking for a
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criteria Prior expertise in the application of DFT and/or expertise in classical and ab initio molecular dynamics techniques for modeling properties and/or reactivity in solution. Website for additional job
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Tenure Track Faculty Position NYU Pain Research Center and Department of Molecular Pathobiology New York University College of Dentistry The NYU Pain Research Center (PRC) and Department of
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proteins and certain lipids, using protein production and purification techniques, followed by lipid interaction or transport tests. In addition, the researcher will use molecular dynamics, protein modeling
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics