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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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. Familiarity in bio/nanomaterial synthesis, bioimaging, drug delivery, radiochemistry, and/or molecular biology techniques is preferred. Experience working with radioisotopes and small animal models is desirable
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Project on Skeletal Muscle Hypertrophy Mechanisms in Mice The project: The Section for Human and Molecular Physiology invites applicants for a three-year PhD fellowship in Molecular Exercise
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-reciprocity of spin waves Angular Momentum of Magnons Magnetically doped Transition Metal Dichalcogenide Thin Films via Molecular Beam Epitaxy Modeling of a magnonic diode based on spin-wave non-reciprocity in
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dedicated to elucidating the cellular and molecular mechanisms that establish immune tolerance to the microbiota, exploring how dysregulation of these pathways contributes to diseases and disorders in the gut
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 1 month ago
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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Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences | Czech | 3 days ago
their molecular organization remains poorly understood. This PhD project will address this fundamental question by focusing on IWS1, a conserved transcription elongation factor that functions as a central
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). More information on the IMPRS faculty: https://www.molgen.mpg.de/IMPRS/fac . The mission of the Max Planck Institute for Molecular Genetics (MPIMG) is to lead scientific and technological breakthroughs
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Computational , Astrophysics Experiment , Astrophysics Theory , ATLAS , Atomic Molecular and Optical Physics , Atomic Physics , Atomic, Molecular, and Optical Physics , atomic-molecular-optical physics , Atomic
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-learning (ML)- driven and physics-based computational workflows to screen large molecular libraries, predict key electrochemical and physicochemical properties, and deliver ranked shortlists of high[1