204 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" uni jobs at George Washington University
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Director for Educational Support Services, the Learning Specialist will support the Educational Support Services program by performing the following duties: Manages a caseload of at-risk and additional
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Learning platform that provides educational offerings from executive education to industry certifications and upskilling and re-skilling opportunities. The GW RevU Team further oversees the college’s
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can be found at https://careers.gwdocs.com/benefits . Other Information: Special Instructions to Applicants: To be considered, please complete an online faculty application and upload a curriculum vitae
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sensitive and confidential information. ● Ability to work independently and as part of a team. ● Strong computer skills, including Microsoft Office Suite and Google products. Experience with Advance, Luminate
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Translation Use bioinformatics, statistics, data science, and machine learning to build risk models and surveillance tools that connect host immunity, microbial ecology, and pathogen transmission dynamics
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for tenure-track or tenured clinical faculty appointment, beginning as early as Summer 2026. The school is especially, but not exclusively, interested in candidates to teach an Intellectual Property and
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around and/or with machine tools that present certain dangers, and all safety precautions must be followed. This position will require kneeling, crawling, climbing ladders, riding lifts and stairs
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Benefits: The MFA also provides generous health and other benefits, details of which can be found at https://careers.gwdocs.com/benefits . Other Information: Special Instructions to Applicants: To apply
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. Full-time faculty also teach medical students and engage in scholarly activity. Minimum Qualifications: Applicants must be board-certified or board-eligible in Physical Medicine & Rehabilitation (PM&R
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intelligence and machine learning to support systems engineers in their work. · Techniques and metrics for designing and evaluating explainable, interpretable, and trustworthy AI-enabled systems · Management