21 chalmers-university-of-technology-material-engineering-phd-polymer-composite Postdoctoral positions at Brookhaven Lab
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. The EIC will be a discovery machine for unlocking the secrets of the “glue” that binds the building blocks of visible matter in the universe. The machine design is based on the existing and highly optimized
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must have completed all degree requirements by the commencement of the employment. BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a
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Apply Now Job ID JR101897Date posted 07/07/2025 The Condensed Matter Physics and Materials Science Division (CMPMSD)at Brookhaven National Laboratory conducts a wide-ranging research program
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(UNC). In addition to BNL, it includes collaborators at Emory University, North Carolina State University, the University of Pennsylvania, Princeton University and Yale University. The successful
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Brookhaven National Laboratory’s Environmental Science and Technologies Department. The selected candidate will join the BNL’s Center for Multiscale Applied Sensing team primarily as part of the new Southwest
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year depending on performance and availability of funds. Candidates must have received a Ph.D. by the commencement of employment. BNL policy requires that after obtaining their PhD, eligible candidates
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Requirements: Required Knowledge, Skills, and Abilities: Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics, physics) awarded within the last 5 years. Strong
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the department on new potential collaborations. Position Requirements: Required Knowledge, Skills, and Abilities: Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics
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achievements, and engage within and beyond the group on new potential collaborations. Required Knowledge, Skills, and Abilities: Ph.D. in computer science or a related field (e.g., engineering, applied
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. in computer science or a related field (e.g., engineering, applied mathematics, statistics) awarded within the last 5 years. Strong theoretical understanding and practical experience in deep learning