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, machine learning, or related fields. Have strong programming and computational skills in Python, R, MATLAB, or related analytical and machine learning frameworks, such as PyTorch, TensorFlow, or Scikit
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: Deep commitment to learning about the natural world, biodiversity, and conservation. Independent: Comfortable working outdoors, when necessary, in the UM-Dearborn Environmental Study Area. Core Skills
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community health concerns and incorporate this information into the evaluation of potential health risks associated with environmental exposures. Learning Objectives: You will have the opportunity to: Gain
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activities, learning how to organize and synthesize information from diverse scientific programs. Under the guidance of a mentor you will perform a structured gap analysis to identify unmet research needs and
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disease burden. Using these findings, you will learn to develop analytic approaches and research products that strengthen the Registry's ability to monitor ALS nationally and support evidence-based research
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About Us The School of Science and Technology at Nottingham Trent University (NTU) is an exciting multidisciplinary environment for learning, teaching and research, with some of the best facilities
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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and
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problems that affect Americans every day from field to table. Learning Objectives: Under guidance of a mentor, the participant will: Learn fundamental and applied concepts in grapevine physiology, molecular
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Center for Devices and Radiological Health (CDRH) | Silver Spring, Maryland | United States | about 23 hours ago
focused on the development of methods and tools in support of our regulatory science efforts in evaluating computational pathology (CPATH) devices. As a fellow, you will have the opportunity to learn about
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outputs, and nowcasting model products for hazard prediction workflows. • Develop and apply machine learning–based post-processing methods to enhance forecast skill for convective hazards. • Perform