136 cloud-computing-"https:"-"https:"-"https:"-"https:"-"https:"-"BioData" positions at NIST in United States
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, or techniques that will speed up analysis times, provide increased information to the chemist, and/or simplify data interpretation while enhancing data quality. One of the goals of the forensic program at NIST is
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recognition; Multivariate statistics; LC-MS analysis; Computer programming; Data analysis; Chemometrics; Principal component analysis; D-partial least squares; Eligibility citizenship Open to U.S. citizens
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components. To develop this program in oxide electronics, a successful applicant will have a solid background in programming (Matlab, Python, or equivalent). Experience with any of the following lock
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generation magnetic data storage. Research projects will include using X ray and neutron scattering to characterize the fidelity of the block copolymer structure to the template and computer simulations of
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-computer interactions such as curation and information retrieval. key words Ontologies; Natural Language Processing; Machine Learning; Artificial Intelligence Eligibility citizenship Open to U.S. citizens
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variables. Computer-controlled equipment is available for alternating-current magnetic-susceptibility measurements as a function of frequency, temperature, and magnetic field. An automated vibrating sample
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RAP opportunity at National Institute of Standards and Technology NIST Applied Mathematics of Soft, Fluid, and Active Matter Location Information Technology Laboratory, Applied and Computational
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., biomarkers, metabolites) must be evaluated using digital twins of breath device prototypes. Our digital twins are based on simulations using computational fluid dynamics (CFD) and computational fluid and
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classification of scientific publications by their relevancy have been done at TRC. A successful applicant is expected to have a strong background in computer sciences, particularly in AI, NLP, and ML. No specific
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of the constraints on sequencing (read length, depth), and informatics (e.g., database composition, algorithm biases). Proposals should address these challenges with strategies to evaluate the metagenomic