49 parallel-computing-numerical-methods "DIFFER" Postdoctoral positions at Michigan State University
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other institutions including the U.S. Department of Agriculture and several universities to improve upon existing remotely sensed data, develop new methods for detection of land management practices
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a variety of methodological backgrounds, which is reflected in the mixture of quantitative and qualitative research methods we are using for this project. One important goal of our research is to
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, CST Numerical EM modeling with Matlab or equivalent software Experience with lab equipment such as VNA, signal generators and testing of radiating devices in anechoic chambers Required Application
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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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substantial training and demonstrated experience in ethnographic and qualitative fieldwork methods, including in-depth interviewing and participant observation; The applicant must show evidence of scholarly
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independently Confidence with computational biology including use of programming languages such as R, python and some familiarity with high performance computing Excellent communication and interpersonal
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microscopy, -omics technologies, and high-performance computing. In addition, Dr. Topp is spearheading the development of a new X-ray imaging facility with focus on non-destructive, high-resolution
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measurements, combining femtosecond pump–probe methods, wide-field imaging, and advanced statistical and computational analysis to elucidate structure–function relationships in biological systems. Candidates
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-performance computing. In addition, Dr. Topp is spearheading the development of a new X-ray imaging facility with focus on non-destructive, high-resolution analysis of root growth and soil interactions
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, recharge, and subsurface flow in intensively managed fields. This position emphasizes the use of noninvasive geophysical methods to characterize spatial and temporal variability in soil moisture