130 computer-programmer-"Multiple"-"U"-"O.P"-"U.S"-"Prof" PhD positions in United States
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candidate with a strong background in computational fluid dynamics (CFD) and specialized expertise in hemodynamics associated with coronary artery disease (CAD). The ideal candidate will hold a PhD in
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, Pennsylvania 19004, United States of America [map ] Subject Areas: Industrial Engineering Mathematics Physics Economics Management Science & Engineering (more...) Computer Science and Electrical Engineering
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/Computer/Mechanical/Materials/Nuclear Engineering or related discipline. • Excellent foundation in materials processing • Hands-on experience with device and system characterization. • Experience in
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, metastasis, functional genomics, therapeutic target development, and cancer proteomics. Submit a full-length CV, a 3-page future research plan, and the names and contact for 3-5 references Required
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. 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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an excellent compensation package, and a broad range of employee benefit plans, including immediate participation in the University’s retirement plan. Staff members are typically eligible for four weeks paid
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the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly. The University also offers a comprehensive benefit program to eligible
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Caltech is a world-renowned science and engineering institute that marshals some of the world's brightest minds and most innovative tools to address fundamental scientific questions. We thrive on finding and cultivating talented people who are passionate about what they do. Join us and be a part...
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
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involved in analyzing data collected from the TexNet seismological monitoring program and other stations or assets that provide quality data. Comparing different methods and tools for moment tensor inversion