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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 22 hours ago
USNH Employees should apply within Workday through the Jobs Hub app The Research Assistant will provide assistance with digitizing, coding, use of OCR (Optical Character Recognition) software
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Position Announcement We are seeking motivated university students to design, build, and deploy no-code AI solutions using Cerbrec Graphbook to address real-world operations management challenges
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to improving the quality and efficiency of the consortium code base. Preference will be given to candidates with a strong publication record and proven experience in Python programming, source code versioning
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transfer, non-equilibrium phenomena in realistically large solid/solid, solid/liquid, solid/gas interfacial systems. Code implementation of spectroscopic modules in electronic structure theory software
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related field. Experience with finite element simulations and developing constitutive models. Knowledge of high temperature creep crack growth. Knowledge of engineering design codes such as the ASME Boiler
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& coordinates conduct of daily activities of research studies, as well as scheduling and follow-through of study visits, procedures, & other testing; participates in coding, data management (includes
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to translate logistical constraints into efficient, scalable code capable of high-speed, real-time decision-making. Integration Support While the programmer is not responsible for executing the physical or low
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investigation of ultrafast charge transfer, non-equilibrium phenomena in realistically large solid/solid, solid/liquid, solid/gas interfacial systems. Code implementation of spectroscopic modules in electronic
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program exploring drivers and seasonality of WNV in a multi-species system. They will write code, use models and other quantitative or statistical analyses within life science, biological, or health
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) 13 TV-L FU reference code: ONEMuc-FluBind2 The collaborative project ONEMUC – Respiratory Mucus as a One Health Interface investigates how the composition and structure of mucosal barriers (mucus