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master degree within preferentially reservoir engineering, or within applied mathematics, computational engineering, scientific machine learning, preferably acquired recently; or who possess corresponding
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to high-performance computing facilities and datasets from laboratory experiments will be provided to support simulation and verification of the resulting model. Replicate and learn a theoretical model for
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 1 hour ago
interest in mental health, suicide prevention, health professions training, and/or military health, as demonstrated through any or all of the following: A record of scholarly publication and presentation in
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-dimensional statistics, machine learning theory, or more broadly, mathematical foundations of AI. The appointment will be for up to two years with annual renewal based on satisfactory performance and continued
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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qualification; (ii) demonstrate research skills in imaging science and machine learning, particularly on image reverse engineering, fake image and video detection, statistical detection models and mathematical
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of at least some of the following: – Extensive independent research experience – Creativity and independence – Experience analyzing hyperspectral data and developing machine learning models - Genetic
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of induced pluripotent stem cell-based human disease models 2) Understanding the role of immunity during tumorigenesis as well as disease relapses in order to design novel inhibitors, CAR-T cell therapy and
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-dimensional statistics, machine learning theory, or more broadly, mathematical foundations of AI. The appointment will be for up to two years with annual renewal based on satisfactory performance and continued
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2). Vascular network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering The Disease Biophysics Group is a creative, transdisciplinary group of engineers