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biology, reef ecology or related fields. Demonstrated fieldwork experience/skills on coral reefs (e.g., diving, deploying instruments, underwater data and sample/image collection; operating research vessels
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imaging, in vivo electrophysiology, animal behavior experiments, animal surgery, computational modeling of animal behaviors, or computational modeling of neural dynamics. Some programming skills for data
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Researcher to join our interdisciplinary team in the Department of Electrical and Computer Engineering. This role focuses on developing and applying label-free imaging techniques, designing cutting-edge optics
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Research FieldComputer scienceEducation LevelMaster Degree or equivalent Research FieldEngineeringEducation LevelMaster Degree or equivalent Specific Requirements - Master’s degree in Computer Engineering or
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University of California, San Francisco | San Francisco, California | United States | about 23 hours ago
DIAG IMAGING MANAGEMENT Full Time 87190BR Job Summary UCSF's Pediatric Radiology Program includes the most advanced availabile imaging technologies in an environment that is safe and comfortable
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contribute to developing and/or applying artificial intelligence, machine learning, and image segmentation and/or data science-based methods in medical imaging processing. Salary Range: $47,000 - $70,500
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candidates who have defended a thesis related to political social sciences. Required skills: - Quality of the scientific record and relevance of the thesis work to the FOCALE program - Methodological agility
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21 Dec 2025 Job Information Organisation/Company University Rovira i Virgili Department Computer Engineering and Mathematics Research Field Computer science » Informatics Researcher Profile
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lab. In addition, you will assist in training new researchers within the research group. You will provide support in processing data generated from 3D motion capture techniques and medical imaging. You
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computer vision, image/video processing, or generative modeling is highly desirable, as is familiarity with LLMs and diffusion models. The successful candidate will collaborate with Prof. Stefanos Zafeiriou