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level. Knowledge of NCAA rules regarding equipment and apparel preferred Proficiency with applicable computer software programs (e.g., inventory tracking systems) ● Strong interpersonal skills
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INFORMATICA - SCIENZA E INGEGNERIA | Italy | 3 months ago
resource optimization in disaggregated Open RAN networks. Where to apply Website http://www.unibo.it Requirements Additional Information Eligibility criteria to apply for research grants fill out the form
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engineering Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions Application Deadline 17 Apr 2026 - 12:00 (Europe/London) Country Cyprus Type of
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, including preparing MFIN and Undergraduate students for careers in finance. This includes the mentoring of students to be career ready and networking with recruiting partners and organization of regular
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, education, licenses, specialty, training and internal pay comparison. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of
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the management, coordination, improvement, growth and assessment of signature programs (Scrappy's Pitch Competition, KSU IDEA network, etc). 4. Coordinating workshops, competitions, events, celebrations, and other
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of remote electronic access control devices, door locking hardware, and related networking equipment Working knowledge of mechanical and electronic key system hardware Knowledge of methods, practices, tools
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experience. Capability to learn software (e.g. spreadsheets, word processing), as well as computer-based inventory management system and other server-based systems. Familiarity with computer-controlled
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#CA-DK Under the direction of a qualified physician, the CT Technologist will operate a variety of equipment, including an x-ray generator, patient table, control console and computer. The incumbent
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Neutral Infrastructure (dfCO2), this role contributes to Program 4: Machine Learning for Carbon Performance (https://dfco2.org.au/program_4 ) that aims to advance the next‑generation AI methods to model