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Field
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relevant to the position. Research Fellow I: PhD from an accredited institution in Agronomy, Crop Science, Soil Science, Agricultural Engineering, Data Science, Remote Sensing, or a closely related field; no
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, particularly Python; (ii) use of parameter optimization algorithms, particularly PEST and PEST++; (iii) remote sensing applied to the water cycle; and (iv) application of machine learning techniques to spatio
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project deliverables are met. Any other ad-hoc duties assigned by Supervisor. Job Requirements PhD in Geography, GIS, Remote Sensing, Environmental Science, Earth Science, or related disciplines. Strong
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and remote sensing datasets for model validation. Develop new functionalities in the Community Land Model (CLM) within CESM. Conduct model simulations to investigate how the tropical atmosphere responds
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for remote sensing and uncertainty estimation. Candidates must have a strong programming background. Requirements: PhD in Computer Science or a related field with a strong emphasis on machine learning
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the model to constrain future calving losses from the Antarctic Ice Sheet. Candidates are expected to hold a PhD in glaciology or related discipline, including experience of remote sensing and/or numerical
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of QRI Fellow Mentors can be found here: https://quantum.umich.edu/fellows/ . Open to all quantum science and technology disciplines, including spectroscopy, photonics, devices, sensing, computation
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based within the Supporting Transition and Employment Pathways Research Lab (STEP; https://step-lab.ssw.umich.edu/ ), an interdisciplinary research group dedicated to advancing disability inclusion by
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with remote sensing applications (e.g., InSAR, thermal IR). Experience in teaching, supervision, or scientific outreach. Please note We do not expect any single applicant to possess all desired
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large, multi-institution, project to advance the remote sensing of freshwater resources. The research will be conducted at the Environmental Remote Sensing Laboratory, under the direction of Dr. Hongxing