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RUTGERS CANCER INSTITUTE VISION, MISSION, AND CORE VALUES: VISION: Through our science, our evidence-based actions, our openness, and our respect for those we serve, we will advance cancer-focused research
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! Be
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
machine learning applied to natural language processing, computer vision, or a related area. Strong publication record in NLP, ML, or related areas -Strong programming skills, including TensorFlow and/or
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vision. Understanding or willingness to learn advanced statistical modeling is a plus Assessment criteria and other qualifications: This is a career development position primarily focused on research
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Deadline 4 May 2026 - 23:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Jul 2026 Is the job funded through the EU Research Framework Programme? Not
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, large language models, or computer vision is preferred Knowledge, Skills and Abilities: · Teamwork: Ability to collaborate with others and contribute to a team environment · Communication
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Post Doc Res Assoc Job Summary The Ho lab at the University of Utah is launching an ambitious program to systematically discover, map, and therapeutically harness mitochondrial microproteins
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, and financial security. Benefits include medical/vision, dental, flexible spending accounts, life, disability, retirement, family life support, employee assistance program, onsite health clinic, tuition
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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for the candidate The candidate will not only deepen and enrich their expertise in AI and computer vision, but also become familiar with using AI to handle curvilinear features which are ubiquitous in many domains