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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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or connectivity analysis; machine-learning or deep-learning methods for geospatial analyses; ecological or remote-sensing fieldwork, particularly in alpine environments; Google Earth Engine, geodatabases or cloud
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goals will also be explored during the later stages of the selection process. You should also have: solid knowledge of artificial intelligence and machine learning techniques, including their limitations
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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