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, conference, competition etc. by contributing technically and/or administratively. Essential Qualifications: ● PhD in computer science/engineering or electrical engineering with expertise in hardware
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Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a wide range of material parameters. The CFN develops and utilizes
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learning and computational materials science. Candidates must hold a Ph.D. The position is in-person only. Candidates should provide a short cover letter and a CV. In compliance with NYC's Pay Transparency
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Details Posted: 17-Jun-24 Location: Clinton, New York Salary: Open Categories: Academic/Faculty Social/Behavioral Sciences Internal Number: CF6440CD-C70C-4BCC-B4A898545282B977 The Women's and Gender