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knowledge-grounded reasoning with flexible machine learning Tools that reduce manual burden while preserving traceability and clinical interpretability This position offers the opportunity to publish novel
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
highly motivated AI Scientist (f/m/x) (best: Computational Pathologist / Machine Learning Scientist for Digital Pathology) to join our efforts in developing AI-driven virtual staining pipelines for cancer
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Location Lexington, KY Grade Level 12 Salary Range $62,400-111,634/year Type of Position Staff Position Time Status Full-Time Required Education PhD Click here for more information about equivalencies: https
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paradigms. We are also leveraging several analytical tools such as computational modelling and machine learning. As a Research Assistant, you will help collect, analyse and interpret EEG data collected in
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 14 days ago
); and propagation of physics-traceable soil moisture uncertainty into precipitation estimates. Machine learning approaches are welcome as tools within this framework — for example, learning the space–time
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advance machine learning and natural language processing (NLP) methods to analyse complex information manipulation, legal responses, and opposition actors across critical domains such as election integrity
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whose scholarship or teaching connects to the mathematics of artificial intelligence and machine learning. The teaching load is two courses per semester. Bowdoin is particularly interested in candidates
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 2 hours ago
Posting Details Posting Details Position Title Assistant Professor - Clinical Psychology External Link to Posting https://jobs.uncw.edu/postings/40782 College College of Science and Engineering
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the candidate's field(s) of research and in career readiness. KSU uses a differentiated workload model. The standard teaching load is 3/3. Teach courses of various sizes including large class sizes; in various
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-on learning environment. Students have access to a fully staffed machine shop, fabrication laboratory, digital prototyping facilities, and dedicated capstone and project workspaces. Research, project