91 computer-"https:"-"APOS-UFFICIO-CONCORSI-DOCENTI" "https:" "https:" "https:" "https:" "https:" positions at University of Virginia
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to a maximum of 39 weeks. One-time incentive payout of $2,500.00 with first 13 week assignment only Please visit: https://hr.virginia.edu/uva-health-internal-traveler-program Opportunities are available
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: This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs. The position will remain open
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is limited to 1500 hours of work in a year. For more information, refer to the Wage Employment link: http://uvapolicy.virginia.edu/policy/HRM-029 To apply, please submit an application online at https
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science, computer science, or a related discipline is required by the start date. Candidates should have strong Python and geospatial-data analysis experience, demonstrated independent research ability, and
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wellness program featuring activities to earn up to $500/year For this position, the selected candidate will need to complete the required background checks prior to the start date of the position. Physical
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development **Contact:** For questions, contact Health System Talent Recruiter, Ashlyn Trant, at hyf5sf@virginia.edu. **Learn More:** For more information and to apply, visit: - [UVA Health Jobs](https
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ongoing departmental research projects. The overall goal of this program is for each Fellow to acquire foundational knowledge and principles of study design, conduct, and data analysis; gain exposure
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customers and associates. Able to communicate effectively over the phone, in person, email, etc. Strong organizational and computer skills. Problem Solving Intuitively able to reason, analyze information, and
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application process, please contact Eric Allen, Academic Recruiter at uth9qh@virginia.edu . PHYSICAL DEMANDS: This job requires extensive computer work, patient interaction, and the ability to traverse
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multidisciplinary experience in combining integrative computational immunology – data-driven, state-of-the-art single cell resolution and spatial methods, machine learning and kinetic modeling – with integrative