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: 276110766 Position: Postdoctoral Research Associate Description: A Postdoctoral Research Associate or more senior research position in computational biology is available in the Pritykin lab at the Lewis
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developing and delivering research proposals • Potentially co-develop or co-teach courses in IE Required Qualifications • Ph.D. or equivalent degree in Industrial Engineering, Statistics, Computer Science
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: · MATLAB · Python · ROS · Computer vision and/or YOLO · Pytorch and/or Tensor Flow · LiDAR · GIS · GNSS receivers Minimum Qualifications: Doctoral degree in Mechanical Engineering, Electrical Engineering, or
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biological chemistry are encouraged to apply. Additional information about the PATS program as well as descriptions of our academic programs and research interests of faculty may be found at www.bu.edu
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
the Renaissance Computing Institute (RENCI), we use data, creativity, and inclusive teaming to revitalize how science is done. Fostering data science expertise and creating cyberinfrastructure isn’t just about
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University of California, Berkeley, Department of Electrical Engineering and Computer Sciences Position ID: University of California, Berkeley -Department of Electrical Engineering and Computer
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Job Description The Department of Computer Science, the Department of Electrical and Computing Engineering, and the Innovation Campus at Virginia Tech will be jointly hosting a Postdoctoral
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with experience in the following biomedical engineering fields: Biomedical photonics/optoelectronics Biomedical nano- and microscale systems/fabrication Biomedical computation/modeling These positions
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format successfully. Position Summary The group of Dr. Han Xiao at Rice University is looking for Postdoctoral Research Associates with experience in cell and protein engineering to join this project
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials