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fluid dynamics. The successful candidate will be expected to work on all or a subset of the above topics, be proficient in working with large data-sets (observational or numerical), machine learning, and
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at https://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty mentor including (but not limited to): Study Development: Conducting literature review, designing studies
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the CliMA team at Caltech for development of a new wildfire module; Generation of reports and scientific publications; Engagement with students and postdocs and provision of technical support within the UNR
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: https://academicpositions.harvard.edu/postings/14695 Applications accepted through March 3rd. Share this post: Tags: Teaching Opportunity , Unique Postdoc Opportunity Return to blog Categories
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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate: 01.02.2026 | Working hours
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
the development and implementation of machine learning models Special Physical/Mental Requirements Special Instructions For information on UNC Postdoctoral Benefits and Services click here Quick Link https
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for a diverse population of undergraduate and graduate students from across the US and the world, as well as crisis intervention in our Wellness Exchange walk-in clinic. Postdocs also spend part of
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. The project takes an explicit social science approach and aims to use Machine Learning and Social Network Analysis methodology to 1. analyze the current and developing opinions of new clean energy technology
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enhance machine learning performance; novel chip design strategies prioritizing efficiency and cost; verification of digital designs; advancements in electronic design automation (EDA), especially for AI
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the ability to quickly learn new things and work independently, along with previous research experience in at least one of the following areas: 1) statistical genetics/genomics/omics, or 2) deep/machine