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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
Title MATRIX Post-Doc Research Associate Vacancy ID PDS004609 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC Position Location Virginia, US Hiring Range
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(data assimilation, machine learning, etc.) Writing proposals / securing external research funding Writing and submitting scientific papers Leading a research group Supervising students Participating in
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Schedule: Monday – Friday, 8 a.m. – 5 p.m. Summary The Cheng Lab at Baylor College of Medicine is searching for highly motivated and talented post-doc candidates to work on Bioinformatics and Computational
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the intersection of machine learning and genomics. The project involves the development and application of advanced machine learning and deep learning techniques to understand the sequence-function relationships
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to three full-time Post-Doctoral Associate (9546 Post-Doctoral Associate) positions. For more info on the division, visit http://www.sph.umn.edu/academics/divisions/biostatistics/. The Post-Doc will work
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Position Details Position Information Recruitment/Posting Title Post-Doc Associate (Barr Lab) Department Human Genetics Inst of NJ Salary Details Offer Information The final salary offer may be
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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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Job Description Apply now Req Id: 37109 Job Title: Post Doc Research Associate City: West Lafayette Job Description: Job Summary We are seeking applicants for a postdoc position that offers a unique
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required. Job Type: Full Time Rank: Post Doc Campus: Unionized Position Code: Not Applicable Job Description: The Mathematics Department at Syracuse University seeks to ll one 12-month Postdoctoral Scholar
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position in statistics, machine learning, and data science. The postdoctoral researcher will be mentored by Professor Yiyuan She and will contribute to the development of innovative statistical methods and