106 parallel-and-distributed-computing-"Computer-Vision-Center" Postdoctoral positions at Michigan State University
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Natural Science and the College of Engineering. CMSE centers around computational approaches, encompassing algorithm development, high-performance computing, scientific modeling, and data science
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, biodiversity), U.S. agricultural and conservation policy, and / or Process-based ecosystem models and their outcomes Knowledge of statistical analysis, and experience using one or more statistical computing
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. The selected candidate will work with Dr. Yuzhen Lu to develop and test automated field-deployed sensing/harvesting systems that may integrate machine vision, artificial intelligence, and mechanisms for
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identity, national origin, citizenship, age, disability or protected veteran status. Required Degree Doctorate -Electrical and Computer Engineering or related field Minimum Requirements Experience with HFSS
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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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conducting and analyzing molecular dynamics simulations Experience using high-performance computing platforms Experience developing neural network models Experience using AI-assisted coding tools for
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lake biota and harmful algal blooms at the continental scale (funded by the National Science Foundation). This postdoc will be at the center of a new initiative turning 51 years of Michigan lake and
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policy, agronomy, or a related field Desired Qualifications Strong skills in satellite remote sensing, GIS, and statistical analysis. Experience using cloud-based computing resources (e.g. Google
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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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-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