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systems, urban technology, networks science, information, decision and complex networks, computational and infrastructure intelligence, revenue and finance, complex systems architectural design framework
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. Qualifications: - Applicants should have (or expected to get in a near future) a Ph.D. in applied mathematics, electrical engineering, computer science, or other related fields. - Strong quantitative and
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Computer Engineering or a closely related field, completed by the start date of the appointment. Research experience in at least one of the following areas: ● Chip design, tape-out, and testing
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conducting research, all with the goal of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and
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-Provost SubDivision-Department: UNT-College of Engineering Department: UNT-Computer Science & Engineering-130310 Job Location: Denton Salary: Salary is commensurate with experience FTE: 1.00 Retirement
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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environment. You will play an integral role in the development of PiFM and closely collaborate with other scientists across the network of NSRCs for synthesis, device fabrication, theoretical calculations, and
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Classification Title: Postdoctoral Position – Neuroimaging - Developmental Network Neurobiology Laboratory Job Description: The University of Florida, Department of Pediatrics, Neuroimaging
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Posting Information Posting Number FAE1828 Advertised Title Post-Doctoral Researcher in Water Resources Engineering Campus Location Main Campus (Memphis, TN) Position Number 023802 Category Full
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Chen in the Mechanical Engineering department at Embry-Riddle Aeronautical University specializes in the development and application of computational models for thermo-fluids transport processes