451 machine-learning "https:" "https:" "https:" "UCL" positions at SUNY University at Buffalo
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Metal Shop Posting Number C260035 Posting Link https://www.ubjobs.buffalo.edu/postings/61834 Employer State Appointment Type Classified Appointment Term Permanent/Contingent Permanent Classified Position
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Projects Services Posting Number R260060 Posting Link https://www.ubjobs.buffalo.edu/postings/62016 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade
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Posting Link https://www.ubjobs.buffalo.edu/postings/62034 Employer State Faculty Appointment Term Term Position Type UUP Faculty Posting Detail Information Fiscal Year 2025-2026 Position Summary
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Posting Number R260058 Posting Link https://www.ubjobs.buffalo.edu/postings/61964 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89 Posting
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Posting Number U260029 Posting Link https://www.ubjobs.buffalo.edu/postings/61953 Employer University Affiliates Appointment Term Position Type Posting Detail Information Position Summary The Department
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Department of Epidemiology and Environmental Health Posting Number P260080 Posting Link https://www.ubjobs.buffalo.edu/postings/61888 Employer State Position Type UUP Professional Professional Appointment Term
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P260077 Posting Link https://www.ubjobs.buffalo.edu/postings/62018 Employer State Position Type UUP Professional Professional Appointment Term Term Salary Grade SL4 Posting Detail Information Position
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P260076 Posting Link https://www.ubjobs.buffalo.edu/postings/62017 Employer State Position Type UUP Professional Professional Appointment Term Term Salary Grade SL4 Posting Detail Information Position
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Posting Details Position Information Position Title Assistant Professor, Marketing Department Marketing Posting Number F260029 Posting Link https://www.ubjobs.buffalo.edu/postings/61630 Employer
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learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in porous materials Develop novel machine learning model for predicting