5,075 programming-"https:" "https:" "https:" "https:" "https:" "https:" ";" positions
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analysis. Research areas include, but are not limited to: working with the modeling team, incorporate multidisciplinary resilience research (e.g., 3, 5) into extensions of the mathematical programming
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PhD position in Reversible Programming Languages (MSCA Doctoral Network E-CoRe, DC1), University of Copenhagen The position is doctoral candidate DC1, “Reversible Programming Languages", in the Marie
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Reversible Languages", in the Marie Skłodowska-Curie Doctoral Network E-CoRe. The position is available from 1 January 2027, or after agreement. Job description The Programming Languages and Theory of
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organize and analyze biomedical and healthcare data to promote health for all. More information about BIDS can be found here: https://medicine.yale.edu/biomedical-informatics-data-science/ (Link is
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Genetics, Neurology, and Neuroscience. Exceptional scientists will have the opportunity for academic career progression at the Center. Learn more about our work: https://www.scherzerlaboratory.org
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research and data analysis, and proficient in written and spoken English. Good programming skills (e.g. Python, R, or MATLAB) and previous experience with EEG/fNIRS/fMRI/eye-tracking/computational
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Helmholtz-Zentrum Berlin für Materialien und Energie | Berlin, Georgia | United States | about 1 month ago
perform X-ray spectroscopy measurement at state-of-the-art large-scale facilities. You will perform quantitative data analysis using programming languages such as Python. You will perform preliminary
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and analyze biomedical and healthcare data to promote health for all. More information about BIDS can be found here at: https://medicine.yale.edu/biomedical-informatics-data-science/ (Link is
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Position Summary(Basic Job Function) This is a temporary or an on-call position. Provides technical support. Responsibilities may include computer programming or operations; research support; medical
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resources, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/, https