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, prevention, and education. Core to the success of our mission is the ability to orchestrate multidimensional data, data analytics, and machine learning to create sustainable impact within a framework of
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
Machine Learning Engineer Appointment Type Fixed Term Faculty Vacancy ID FAC0005084 Full-time/Part-time Part-Time Permanent Hours per week 30 FTE 0.75 Position Location North Carolina, US Hiring Range
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related to staff position within a Research Infrastructure? No Offer Description Career Opportunities at UM6P College of Computing: Professor in "Machine Learning". About UM6P and its College of Computing
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Junior Professorship (W1) (for a period of 3 years) of Mathematics of Machine Learning commencing as soon as possible. The primary tasks of the successful candidate include research and teaching on
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. ROLE The Scientific Software Developers applied to Machine Learning report to the ASC and GOCO Directors and are responsible for supporting the ASC and GOCO Division in the design, development, and
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25 May 2024 Job Information Organisation/Company Università degli Studi di Udine Research Field Computer science Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Country Italy Application Deadline 14 Jun 2024 - 23:59...
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of multi-institutional research projects. The Research Computing Center (RCC) seeks to hire an experienced Computational Scientist – Scientific–AI and Machine Learning to serve as a domain expert in
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An exciting opportunity has arisen for an enthusiastic seismologist with expertise in machine-learning workflows for seismic data analysis to develop enhanced earthquake catalogues to support the latest
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Machine learning models for prognosis prediction in periodontal treatment School of Clinical Dentistry PhD Research Project Competition Funded UK Students Dr Vitor Neves, Prof Ali Khurram
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compare the patterns modeled, and demonstrated the relevance of these approaches by integrating them in a brain morphometric method based on machine learning [3]. Recently, we started to explore