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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 15 hours ago
& Computer Engineering Work Location EPIC Vacancy Open To All Candidates Position Designation Post Doc Employment Type Temporary - Part-time Hours per week 40 Work Schedule Pay Rate $48,000 - $53,000 Minimum
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
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, Geography, Civil Engineering, Computer Science, Mathematics, Physics or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning
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Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Researcher -- Scientific Machine Learning (NESAP) to join the Workflow Readiness team as part of NERSC's
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PhD or equivalent degree (e.g., ScD, MD, DVM, DrPH). Under the guidance of Dr. William Pan, the Postdoctoral Fellow will perform full-time, independent research, consistent with preparing for a future
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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of education and related technical/military/paraprofessional experience may be substituted for a bachelor’s degree on a year for year basis. An advanced degree (Masters or PhD) may be substituted
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assimilation, and machine learning frameworks. Expertise in modeling geophysical systems. Strong proficiency in machine learning libraries such as PyTorch. Proficiency in writing clean, efficient, and well
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contribute to overall lab operations. The applicant will be a collaborative, impact-focused problem solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber
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manufacturing and maturation of cells and engineered tissues at low cost, and simple biofabrication technologies to build clinical-scale constructs. Learn more about the innovative work led by Dr. Chris Chen here