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collaborations, market and regulatory analysis, technology transfer, and more. Click through to learn more about each area: Strategic Systems Analysis and Engineering Energy Conversion Engineering Computational
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
Posting Information Posting Details Department Mathematics - 318900 Posting Open Date 10/07/2024 Application Deadline Open Until Filled Yes Position Type Postdoctoral Scholar Position Title
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different disciplines and mentors Stanford Departments and Centers: Medicine, Biomedical Informatics Research (BMIR) Biomedical Data Sciences Postdoc Appointment Term: 1 year minimum with the option to extend
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software engineers within the Computer Science and Mathematics Division, providing an opportunity to work in a stimulating multidisciplinary environment. Major Duties/Responsibilities: Perform neutron
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machine learning, statistics, or applied mathematics that could drive the frontier of biomedical research. The role will be focused on the development of novel computational and algorithmic methods, with a
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approaches to problems in acoustics, lasers, spectroscopy and atomic beams. Our faculty collaborate with colleagues in many other units including Biology, Chemistry, Mathematics and the Brody School
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of infrastructure and technology systems for mathematical/computational modeling and control theory for life-cycle management optimization and policy of smart and sustainable infrastructure and environment systems
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, communications, and updates. Required Education and Experience PhD Degree in computer science, applied/computational mathematics, engineering, bioinformatics, data science, or a related field and two years
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genomics, metabolomics, or microbiome analysis Computer science, particularly machine learning, artificial intelligence, data science, or computational biology Mathematics or statistics, with experience in
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. Minimum Requirements • PhD in a quantitative field, including physics, neuroscience, mathematics, statistics, computer science, or related fields. • Strong quantitative background including at least some