74 high-performance-computing-"Computer-Vision-Center" Postdoctoral positions at Duke University
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supervisor. Understand and comply with all safety standards and procedures to ensure a safe working environment for all laboratory staff. Collaborate with other staff and perform other duties as requested by
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. Occupational Summary This postdoctoral appointment is part of the Duke University Aging Center’s NIA-funded T32 Postdoctoral Research Training Program. This multidisciplinary program is focused on developing
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career. The appointment is not part of a clinical research training program, unless research training under the supervision of a senior mentor is a primary purpose of the appointment. The appointee works
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, genomics, or computational analysis of high-dimensional datasets. Experience with one or more of the following: Flow cytometry Single-cell sequencing Spatial transcriptomics Multiplex imaging Bioinformatics
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appointment is for one year and is renewable, contingent on performance and funding. Required qualifications include a PhD in computer science, statistics, biostatistics, epidemiology, biomedical informatics
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regeneration biology, disease modeling, computational biology, and translational research. Fellows will be encouraged to develop independent research directions, publish high-impact studies, present at national
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Command-line computing High-performance computing environments Candidates with strong computational backgrounds who are interested in developing wet-lab expertise are strongly encouraged to apply. Career
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. This position is best suited to those who enjoy statistics, coding, manipulating and visualizing data, and other quantitative analysis tasks. Work Performed The new researcher will leverage knowledge and skills
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Position Description The DukeNLP group in the Department of Computer Science at Duke University invites applications for a postdoctoral associate position in natural language processing and machine
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the mechanisms of, and interventions for, immuno-senescence and aging in lung transplantation using high-throughput multi-‘omic approaches, primary cell culture systems, and animal models of transplantation. Ph.D