464 computer-programmer-"https:"-"CNR"-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions in United States
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Preferred Experience, Skills, Training/Education: 1. Ph.D. in Industrial Engineering, Biomedical Engineering, Data Science, Computer Science, or related fields. 2. The candidate is expected to have a strong
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Requirements Strong computing and strong background/expertise in clustered data, survival data, causal inference or measurement error are desired. Strong written communications Additional Information: Per
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sophistication, including strong statistical skills and comfort with large-scale or complex data. Experience with computational text analysis, such as NLP methods, historical text processing, topic modeling
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Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, or a closely related field, with a strong research background in AI, reinforcement learning, and multi-agent systems. Demonstrated
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, computer science, architecture, and engineering to develop scalable, data-informed solutions in sustainable design, construction, and energy management. The Cluster aims to modernize—and ultimately revolutionize
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Program (MRNTP) services that provides Referral to UMMC- Level IV NICU Referral to UMMC PICU providing ECMO and post-cardiac surgery care Vermont-Oxford Network. Reporting on Quality Metrics UM SJMC is a
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Posting Details Position Information Job Title Mathematics and Statistics Postdoctoral Fellow Pool Posting Number P0543F Position Summary Information Job Description Summary The Department of Mathematics and Statistics at Auburn University invites applications for several one- or two-year...
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 2 months ago
population genomics, GWAS, and/or QTL analysis. Proficiency in computational/data analysis environments (R, Python, Unix/Linux, HPC systems). Strong communication skills and ability to work effectively within
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treatment-control interference; · Programming/scripting knowledge suitable for processing raw data for analysis (e.g., text manipulation); · One or more computational environments for statistical analysis
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to plan and carry out clinical trials, observational studies, and database analyses. Analyzing quantitative data using statistical software such as R or SAS and going through the code and analytics with