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: Accelerating Real World Data-driven Precision Oncology through Data Science and Informatics Excellence in Research: https://cprit.texas.gov/grants-funded/grants/rr230020 · POI-KB: Design and Development
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26 Jun 2026 Job Information Organisation/Company Université Marie et Louis Pasteur Research Field Computer science Technology Researcher Profile First Stage Researcher (R1) Positions Other Positions
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together DII and Futurity Systems, a Barcelona-based technology company developing AI tools for innovation and competitive intelligence. TOPO-LLM asks whether large language models can reason more
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techniques: identifying the factors that establish early RT at target genes, determining how they promote translocation biogenesis, and testing them in preclinical models. The work combines CRISPR engineering
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device design and system development, with a particular focus on optical nanodevices and integrated systems. New theoretical model development and technology demonstrators, with relevant research lab
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 10 hours ago
Posting Details Posting Details Benefits of Working at UNCW At the University of North Carolina Wilmington, we are driven by a clear purpose: to empower student success, advance innovation, and
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, and problem-solving skills Programming experience in Python or a similar scientific language Interest in machine learning and data-driven modelling Excellent written and spoken
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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mobiltelefonen din. En cookie er ikke et program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få
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, the AI Generalist, and CUIT technical partners, this role will translate requirements into scalable technical solutions using programming, machine learning, large language models, prompt engineering, data