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Strong foundation in quantitative data analysis, statistics, and modeling Basic experience with machine learning or AI; ability and motivation to develop advanced skills during the PhD Knowledge
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
manual dexterity for computer work. Occasional night and weekend work required. Campus Security Authority Responsibilities Not Applicable. Special Instructions Applicants will need to submit a cover letter
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techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
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statistical and machine learning methodologies to analyze and predict aspects of the collected data With the guidance of Drs. Stuber and Bruchas, develop experimental methodologies related to two-photon imaging
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insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Position Description Advertised
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development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program. Visit https://hr.utdallas.edu/employees/benefits/ for more information
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reliability, resilience, and security. Our team is looking for an intern who has strong technical background in machine learning (ML) and artificial intelligence (AI), ideally on large language models, natural
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identity, and gender expression), marital family, and parental status, pregnancy, genetic information, military enlistment, or veteran status, and any other class of individuals protected from discrimination
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have an interest in quality news and AI-based chatbots. We expect: A Master’s degree in either computer engineering or computer science/data science. Experience with AI, Large Language Models, RAG, data
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of written and spoken English. You should have experience with programming (e.g. Python, Julia), simulation methods (e.g. molecular dynamics) and modern machine learning methods. Additional Information