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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
across nearly 30,000 square degrees of sky. This role will work as part of a collaborative and multidisciplinary team to develop software for data analysis, monitoring, and science verification
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 18 hours ago
across nearly 30,000 square degrees of sky. This role will work as part of a collaborative and multidisciplinary team to develop software for data analysis, monitoring, and science verification
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) are strongly recommended. You may upload all three on the application under CV/Resume or upon answering the questionnaire you may attach the documents. Qualifications Required Education Appropriate PhD in
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this role, we are looking for candidates to have the following skills & experience: Essential criteria PhD, or in the final stages of obtaining a PhD, in a relevant area of social science (e.g., sociology
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and resilience. TruX conducts research in software security, software repair, and explainable software to create key practical solutions for developers, allowing them to achieve trustworthiness
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students. Maintain laboratory instrumentation and follow applicable safety standards. Qualifications: Appropriate PhD in Chemistry or related field. A well-qualified candidate may also possess: Experience in
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access to many of the College’s facilities including the gym and pool Free fitness and wellness classes And more! https://www.bowdoin.edu/hr/benefits-perks/index.html Education/Skills Requirements PhD
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to Rui Tang, PhD, Assistant Professor at ruit@wustl.edu . Cover letter expressing your interest and highlighting your relevant experience. Curriculum Vitae (CV) with a list of publications. Contact
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, archives, and archaeological sites to retrieve samples. Support the PI in the preparation of reports and publication of data findings Qualifications PhD in Anthropology Ability to travel extensively
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. Familiarity with standard design verification (DV) procedures and continuous integration (CI) setups would be beneficial. Knowledge of machine learning workloads and the design of machine-learning accelerators