308 computer-"https:" "https:" "https:" "https:" "Univ" "UNIV" positions at Columbia University
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Deadline 1 Mar 2026 - 00:00 (Africa/Abidjan) Country United States Type of Contract Not Applicable Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by a EU
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the medical surveillance program Potential bloodborne pathogen exposure Successful completion of applicable compliance and systems training requirements Equal Opportunity Employer / Disability / Veteran
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the position, please email apam@columbia.edu. Applicants are encouraged to consult https://appliedmath.apam.columbia.edu for more information about the applied mathematics program, and https://apam.columbia.edu
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Qualifications Bachelor?s degree and/or its equivalent. A minimum of two years? related experience. Supervisory experience with a demonstrated ability to program workflow and coordinate schedules is preferred
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maintenance on fans, all types of pneumatic and electro pneumatic building systems computer control interfaces. In accordance with Collective Bargaining Agreement, may be required to respond to emergencies on a
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], electronic instruments, electromechanical equipment, and computers, Manage computer data storage and backup software. Update computing resources as needed. Maintain log books and other records. Assist graduate
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general office responsibilities, the Administrative Assistant oversees the administrative process for Incompletes/Deferred Exams. Will also provide executive level support to the Academic Success Program
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lift patients and supplies Participation in Medical Surveillance Program Contact with patients and/or human research subjects Potential bloodborne pathogen exposure Successful completion of applicable
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technical discipline, or satisfactory completion of university approved training program, or successful completion of University Mechanic Training Program. Preferred Qualifications Must have all applicable
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, implementation, and analysis of machine learning models for computer vision tasks (40%). Analysis of natural scene statistics in aquatic and terrestrial environments (40%). Design of models to learn texture