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achievements in the field of physical sciences documented by publications in renowned journals 2. Additional Requirements: 1) statistical analysis of large data sets 2) knowledge of machine learning 3
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biochemistry, molecular biology, gene therapy, or drug delivery. • Collaborate with the research team to develop and secure competitive grant funding. Applicants should submit the following: 1. Cover letter
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 1 month ago
. Preferred qualifications: D. in Quantitative Genetics/Genomics, Computational Biology, or Related Discipline. Skilled in single-cell transcriptomic analyses, machine learning and artificial intelligence
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
, machine learning and data analytics, multi-objective optimization, life cycle assessment (LCA), serious gaming, and other participatory research methodologies. Candidates should also demonstrate leadership
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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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biosafety and biomedical research-related training and maintains compliance with all safety training and requirements. Acts as a liaison to other departmental personnel, outside investigators, and vendors
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data at lab meetings and at regional or national conferences. Adhere to safety and compliance guidelines. Summarize and write findings pertinent to the research carried out. Support other members
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State University of New York University at Albany | Albany, New York | United States | about 20 hours ago
innovative research and work on projects alongside faculty and researchers at CTG UAlbany. To learn more about CTG UAlbany visit http://www.ctg.albany.edu . CTG UAlbany's research portfolio focuses
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution