48 structural-engineering-"https:" "https:" "https:" "https:" "https:" "University of Hertfordshire" Postdoctoral research jobs at Pennsylvania State University
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underrepresented in STEM fields and other stakeholders will be viewed positively. Candidates should apply online at https://hr.psu.edu/careers . Candidates should provide a cover letter, curriculum vitae, and the
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@psu.edu Visit our website at https://arc.la.psu.edu/ for more information on the Africana Research Center. BACKGROUND CHECKS/CLEARANCES Employment with the University will require successful completion
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with state-of-the-art laboratories. Please see https://www.cee.psu.edu/ for additional information about the department. The College of Engineering at Penn State prepares current and future generations
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to practice veterinary medicine in 1 or more US state(s). The start date for the residency will be July 1, 2026. Applications should be submitted to https://hr.psu.edu/careers and include a cover
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been met for completion of the Ph.D degree prior to the effective date of hire. Interested candidates must submit an online application at https://hr.psu.edu/careers . Please submit your curriculum vitae
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SPECIFICS Postdoctoral Scholar Opportunity Grain Crop Production Laboratory - Department of Plant Science - Penn State University https://plantscience.psu.edu/research/labs/grain-production-lab Position
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correctional research, often in partnership with major research universities and institutes. The CJRC is also connected to the Penn State Department of Sociology and Criminology (https://sociology.la.psu.edu
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and Engineering Department at Penn State University. The candidate will be working on a wide range of materials including beam sensitive materials, 2D materials, and oxides and will have the opportunity
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EHR data. The postdoctoral fellow, under the mentorship of Dr. Dajiang Liu (https://dajiangliu.blog ), is expected to work on at least one of these objectives. Requirements: A Ph.D. in statistics
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the Electrical Engineering department, and Daning Huang in the Aerospace Engineering department in the area of Scientific Machine Learning. The project is to develop computationally efficient reduced-order