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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 30 minutes 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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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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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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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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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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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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) 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