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intelligence models for the analysis of multispectral remote sensing imagery. The main tasks include implementing computer vision and machine learning methods for the detection and prediction of algal blooms in
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willingness to learn A genuine interest in understanding and modeling human behavior Excellent written and spoken English skills *for students with an education earned outside of Sweden, a 4-year Bachelor’s
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and training nonhuman primates; Knowledge of basic computer science and ability to learn to use the computer. Preferred Qualifications Registered Veterinary Technician (RVT) license registered in
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engineering or similar. Knowledge and experience with deep learning models applied in computer vision. Remarkable academic trajectory, validated by a strong record of publications in relevant international
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CU Denver, a place where innovation, research, and learning meet in the heart of a global city. We’re the state’s premier public urban research university with more than 100 in-demand, top ranked
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-friendly university and a great place for veterans to earn their degrees. The Thomas Harriot College of Arts and Sciences (https://thcas.ecu.edu ) is home to 15 academic departments, several
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Posting Summary Logo Posting Number RTF00078PO26 USC Market Title Senior Research Associate Link to USC Market Title https://uscjobs.sc.edu/titles/8218 Business Title (Internal Title) Senior
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enterprise capabilities that impact students, faculty, staff, and research communities worldwide. Learn more about Duke University’s https://hr.duke.edu/benefits/ package. Duke is an Equal Opportunity
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/RTX ) system: Implement statistical and machine learning techniques to augment graph edge properties in ARAX; Create modular python wrappers to interface with NCATS (National Center for Advancing
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Ecole Nationale des Ponts et Chaussées (ENPC) | Champs sur Marne, le de France | France | 3 months ago
-scale (~10’s of km2) permafrost thermo-hydrological hybrid twin, to be coupled with state-of-the-art freezing/thawing soil mechanics machine learning-based surrogate models (Richa et al., 2024, Tristani