317 programming-"INSAIT---The-Institute-for-Computer-Science" positions at Harvard University
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contribute to technical deliverables and help to plan for technology translation. Basic Qualifications PhD in engineering, biomechanics, or a related field. Additional Qualifications Interest in
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experience in modeling of atmospheric composition. Additional Qualifications Experience with the GEOS-Chem model and with inverse analyses, strong scientific programming skills. Experience with inverse
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the Data Science Master’s program and the Area Chair in Computer Science based on need and candidate preference and expertise. Assignments will be taken from a set of courses in machine learning and data
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created the Environmental Fellows program to enable recent doctorate recipients to use and expand Harvard’s extraordinary resources to tackle complex environmental problems. The Environmental Fellows will
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)colonial Indigenous settings in the USA. Responsibilities Under the supervision of Prof. Joseph Gone, Faculty Director of the Harvard University Native American Program, and in collaboration with regional
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advanced research in our fields of study, and advocate for the humanities. Candidates should have a distinguished record of scholarly achievement, as well as significant experience in program management and
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intellectual leadership and impact in a field of study and teaching relevant to Australian Studies. Candidates who are qualified to teach in a department, degree program or field of study offered in the Faculty
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School: Faculty of Arts and Sciences Department/Area: Kempner Institute for the Study of Natural and Artificial Intelligence Position Description: The Engineering Fellowship Program at Kempner Institute
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January 11, for awards is February 1, and for the internship program is February 15. Undergraduate Students Graduate Students and Advanced Undergraduates Post-doctoral Fellows Early-Career Scholars (from
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experience in modeling of atmospheric composition. Additional Qualifications Experience with the GEOS-Chem model and with inverse analyses, strong scientific programming skills. Experience with inverse