787 cloud-computing-"https:"-"https:"-"https:"-"BBMRI-ERIC" Postdoctoral positions in United States
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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI
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computational scientists to advance a next-generation, user-friendly, agentic AI platform for automated data analysis, interpretation, and user interactions. The appointment is expected to last two years and the
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with PyTorch, required to have experience developing code with a team through collaborative version control Experience working with large datasets and cloud computing environments. Solid background in
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how to apply for a faculty or staff position, please review this tip sheet . Relocation Bonus May Be...
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 hours ago
Pharmacology T32 Postdoctoral Training Program Vacancy ID PDS004510 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC Position Location North Carolina, US Hiring Range
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for the DOE Oak Ridge Environmental Management Science Education and Internship Program, you will need to meet the following eligibility criteria at the time of application: Have a cumulative GPA of 3.0 on a
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skills. Experience with cloud computing and big data analytics platforms. Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer. PD; SN Requisition ID: 23791 Apply now
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biological data. · Proficiency in R and/or Python for data analysis and visualization. · Experience working with large datasets in an HPC or cloud computing environment. · Demonstrated ability to work
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with high-performance computing (HPC) environment, cloud-based computation, software tools for genetic epidemiologic analyses (e.g. GWAS, whole-genome sequencing, polygenic score, Mendelian Randomization