114 parallel-programming "Max Planck Institute for Human Development" Fellowship positions at Michigan State University
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, including model setup, process representation, calibration, interpretation of model behavior, and development or modification of scientific modeling workflows Exceptional Fortran programming expertise
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responsible experience in hydrologic, groundwater, or water quality modeling and the development or integration of scientific models Demonstrated advanced programming skills in Fortran and Python
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to): a professional development workshop for current EEB grad students and postdocs; a co-working group; an EEB grad/postdoc-led working group that leads to a published outcome. The Fellows research
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parallel projects will ensure the development of independent projects to support the long-term career goals of the applicant. Generally, the project will center around leveraging bacterial and mammalian
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developmentally appropriate curriculum designed to promote the development of the whole child. The CDL is in the department of Human Development and Family Studies (HDFS) in the College of Social
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primary responsibility for program design and delivery, from developing training schedules, researching resources, to coordinating all logistics and programming activities. Academic advising and support
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description of work/duties: Implementation of computational methods and workflows for a variety of tasks relevant to in silico modeling and drug discovery Development of tools for molecular
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results, and manuscript preparation. Contribute to the development of extramural grants and fellowship applications. Present research findings at scientific conferences. The appointment is for 12
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partnerships and programming, research incubators, and mentorship. As an institution of higher learning, Michigan State University is committed to providing a safe environment for its students, faculty, and
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, processing samples for microbiome characterization, and computational modeling. The Postdoctoral Researcher will be responsible for leading the development of predictive models based on environmental