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Field
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our translational efforts is the development of mRNA-based therapeutics, particularly in vivo CAR-T/NK/Macrophage technologies and cancer mRNA vaccines, as well as epitranscriptomics-based biomarkers
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: Knowledge of kinetic modeling and/or machine learning interatomic potentials. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre-employment background
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position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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Fracture Network (DFN) and Embedded Discrete Fracture Modeling (EDFM) Tracer design and interpretation Machine learning or optimization for reservoir management Experience working with field-scale geothermal
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 10 hours ago
background with evidence of both skills related to convex optimization, machine learning, stochastic gradient descent, and deep learning Demonstrated experience in developing, analyzing, and implementing
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only supports your professional development, but also actively contributes to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide
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Principal Investigator and a cell-culture specialist in a friendly, multidisciplinary group spanning optics, electrophysiology, microfabrication and machine learning, collaborating with partners
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for purposes of collective bargaining and matters affecting your compensation and working conditions. Basic Qualifications PhD in Computational Biology, Bioinformatics, Machine Learning, Data Science, or a
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aberration-corrected electron microscopy, pair distribution function as well as XRD refinement to demystify the microstructure-property of new composition-disordered thermal materials and apply machine
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for cell transplantation therapies in animal models of Alzheimer's disease, stroke, and epilepsy. To achieve this goal, the candidate will combine a gene network-based approach with a machine learning model