253 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" uni jobs at Columbia University
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of outstanding potential to Columbia University. This two-year or 2.5 year fellowship is to begin between July and September 2026. There will be an opportunity to teach a course in the first year of the fellowship
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to sustain an active research and publication agenda and to teach in the departmental undergraduate and graduate programs. Candidates with expertise in machine learning, big data, mathematical finance and
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, nominations, referrals, and CVs with cover letters should be sent via the Isaacson, Miller website below. https://www.imsearch.com/open-searches/columbia-university-mailman-school-public-health/dean Columbia
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, 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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University’s online Academic Search and Recruitment System (ASR). The application can be found here: https://apply.interfolio.com/180101 . Any applications submitted through directly to AJO will not be
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graphene, and state-of-the-art nanolithography and 2D materials techniques. All applications must be made through Columbia University’s Academic Search and Recruiting (ASR) system (https
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for an Associate Research Scientist. Details: https://www.science.hr/jobs/218976/associate-research-scientist-9/ Where to apply Website https://www.science.hr/jobs/218976/associate-research-scientist-9/ Requirements
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student research worker to support AI and machine learning research in cardiovascular health informatics. The position involves working with both structured and unstructured electronic health records (EHR
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in education. Excellent interpersonal and organizational skills. Computer Skills: proficiency with MS Word programs and familiarity with Mac and PC platforms. Experience in clinical research setting
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opportunities for learning new skills to support research Teaching and Training Support (Student and Research-facing) Instruct and train laboratory users on machine shop tools and laboratory testing equipment