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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 11 days ago
environmental monitoring through advanced (bio)chemical sensing, combining electrochemistry and imaging technologies. Led by Prof. María Cuartero (ERC Fellow) and Prof. Gaston Crespo, UCAM-SENS fosters cutting
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 11 days ago
/InstituteUCAM HiTech, Sport & Health Innovation HubCountrySpainGeofield Contact State/Province Murcia City Murcia Website http://www.ucam.edu Street Av. de los Jerónimos, 135 Postal Code 30107 STATUS: EXPIRED X
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ZürichCountrySwitzerlandCityZurichPostal Code8006StreetRämistrasse 101Geofield Contact City Zurich Website https://ethz.ch/en.html Postal Code 8006 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail
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be required to submit employment verification documents on their first day of work. For a list of acceptable documentation, follow this link: https://www.indstate.edu/sites/default/files/media
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-premises environments, creating secure, scalable code and backend services that align with system-wide privacy, security, and accessibility standards. The AI Developer configures monitoring of AI solutions
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part of a dynamic scientific environment with renowned researchers in the fields of hematology and leukemogenesis (https://gencelldis.fr/l-benajiba-team/ https://www.institut-leucemie.fr/en
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for animal experimentation, genomics, imaging and bioinformatics, and strong support for PhD training, career development and international mobility. Where to apply Website https://t.ly/bkiAT Requirements
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participating in staff meetings, stewardship model, and engaging in professional development opportunities. Will work collaboratively with Extension personnel to maintain a positive public image and demonstrate
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
DIAG IMAGING MANAGEMENT Full Time 87118BR 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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experimental design. Proficiency with machine vision and deep learning techniques, including image segmentation, landmark placement and metric learning, for the automation of phenotypic analysis of large image