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Cybersecurity Maturity Model Certification (CMMC) spaces, but will operate within and support both unclassified and collateral spaces. The ISSM will oversee the unclassified and collateral programs at ARL from a
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supervision of 8-15 employees in 3-4 buildings with 600-1,000 residents. As an incoming team member of Auxiliary and Business Services, it will be expected that all employees embody and model Penn State’s and
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cloning, computational modeling, tissue culture, and flow cytometry. BACKGROUND CHECKS/CLEARANCES Employment with the University will require successful completion of background check(s) in accordance with
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processing techniques, such as cold sintering, and requires strong skills in kinetic modeling and experimental design. The candidate will contribute to developing new workflows for electroceramics, optimize
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development of pricing models, cost-recovery calculations, and revenue projections for facility-based activities. Coordinate logistics for external facility use, including space requests, schedules, technology
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resource program to ensure efficient and effective use of funds, increasing cost recovery, and proforma financial modeling Oversee and manage the annual cost recovery efforts including service line
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interpreting and adhering to sponsor and University guidelines, resolve issues related to contract compliance; correspond with sponsors and sub-recipients regarding performance problems. Qualifications
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of this position is flexible and can operate fully remote within the United States, fully in-person at our University Park Campus, or in a hybrid model of both in-person and remote. Standard working hours are in
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at the University Park campus, or in a hybrid model of both in-person and remote (e.g., 2 days remote, 3 days in the office per week). Standard working hours are in the Eastern time zone. Questions about flexible
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%): Identify, evaluate, deploy, and maintain a suite of relevant open-source software and platforms to support AI modeling, simulation, data visualization, and collaborative development (e.g., MLflow, GAMA