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Website: https://engineering.uark.edu/ Summary of Job Duties: The Postdoctoral Fellow - Biomedical Engineering will continue investigation of cancer nerve crosstalk in both breast cancer and pancreatic
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: This project is related to machine learning for Urban Informatics. In this context, the intersection between the urban infrastructure and digital technologies plays an essential role. The aim is to develop
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Postdoctoral Research Associate (Electrical and Computer Engineering) Posting Number req24681 Department Electrical and Computer Engr Department Website Link https://ece.engineering.arizona.edu/ Location Main
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focus on processing and utilising machine-learning techniques to analyse large volumes of data from sensors installed in Phase 1. The aim will be to merge the QC points and tracking system developed in
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Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP) | Paris La Defense, le de France | France | about 2 months ago
a postdoctoral researcher to work full-time on the DiscoReel project. The postdoc will work on developing machine and deep learning methods for epidemic modeling, integrating them with mechanistic
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world are facing dramatic upheaval as a result of rapid technological change driven simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic
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applications for postdoctoral research fellowship position(s) within the field of machine learning, natural language processing, and AI safety. The proposed starting date is 1 February 2026 or soon thereafter
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team member in the CBSC focused on ligand discovery, joining a team of dedicated computational researchers with diverse expertise ranging from structural bioinformatics to machine learning and AI. Your
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approaches. Machine Learning in Geotechnical Engineering: Utilising data-driven approaches to model and predict soil-structure interactions or other complex geotechnical problems. Reliability-Based
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work closely with I-CREWS researchers across the state. The position emphasizes developing, integrating, and applying modeling approaches—including machine learning (ML), hydrologic and energy systems