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institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Computer Vision offers two full-time positions as Research Associate / PhD Student (m/f/x
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experience in small animal diagnostic imaging. B2 Masters, PhD [or other evidence of research training]. Skills Essential: C1 High standard of communication skills, both oral and written. C2 Ability to work
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computational sub-team that includes computer scientists and computational PhD students, fostering an interactive environment of technical exchange, code review, mutual support, and collaborative problem-solving
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
, state of the art imaging technology, and translational research centers, including the Imaging Center for Intelligence (Ci2). Required Qualifications Bachelor’s degree in computer / computational / data
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criteria. Program Website: https://orise.orau.gov/fbi/ Applicants should have received their Bachelor, Master, or PhD degree within the last 5 years of the start date. Students may apply for the program
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. Where to apply Website https://fhnp.es/ofertas-de-empleo/ Requirements Research FieldMedical sciences » OtherEducation LevelPhD or equivalent Skills/Qualifications Qualification: PhD, preferably in
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Job Purpose To deliver an efficient and effective Diagnostic Imaging Service by providing expertise and clinical activity in the Small Animal Hospital. To enhance and develop the delivery
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Research Investigator Job Profile Title Research Investigator, Senior Job Description Summary The successful applicant will be knowledgeable in methods of mouse model generation; Dissect, process, mount
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, pharmacology, cell and molecular biology, imaging and nuclear medicine, ophthalmology, rehabilitation, tissue engineering, food animal, equine, and small animal medicine and surgery, and others. Research
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-to-date taxonomic expertise and exposure to innovative and automated image processing and morphometric techniques, as well as fossil identification involving Artificial Intelligence. A pilot study will be