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communicative skills in English, both in writing and speech.Desirable Comfortable with prototyping experiments using motion capture and virtual reality devices, 3D animation software, and relevant programming
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electronics, the control software, and the SVT ePIC DAQ chain. The candidate will also be strongly involved in the characterization phase, which requires the use of a wafer probe for prompt feedback
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multimodal data (video, self-report, physiological sensors, automatic facial recognition software) that examines CER in multiple contrasting contexts. And (3) Advance educational theory and practice by
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disinformation. Working closely with interdisciplinary university/industry teams including psychologists, data scientists, and software engineers, the researcher will contribute to our expanding research program
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
, and testing of detector components using the UNH test stand. Analyze test beam and cosmic ray data to characterize detector response. Collaborate with hardware engineers and software developers
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of the BMS in lithium-ion batteries, including sensors, actuators, and controllers. In our facility, we are establishing a research unit focused on developing the necessary hardware and software components
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(in vitro and/or in vivo). • Proficiency in relevant software for data analysis and structural visualization. • Experience with in-silico discovery of antimicrobial
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dynamics, and materials chemistry. Strong Python programming skills are required, and prior experience with developing open-source software or databases will be considered a plus.Candidates should apply at
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. Preferred backgrounds include nonlinear optics, quantum optics, spectroscopy, or instrumentation. Proficiency in software and coding (e.g., MATLAB, LabVIEW, Python) is expected. Applicants with a strong
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Demonstrated experience with LS-DYNA or comparable commercial FEA software Proficiency in Python programming for scientific computing and machine learning applications Experience with machine learning methods