246 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions at University of Minnesota in United States
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opportunities through professional training and degree-seeking programs supported by the Regents Tuition Benefit Program Low-cost medical, dental, and pharmacy plans Healthcare and dependent care flexible
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/computer engineering, materials science, physics, or closely related); PhD strongly preferred. Eight years relevant experience with 5+ years leading government-facing microelectronics R&D (DoD/NIST/Service
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. This position does not offer a STEM OPT training program. The University of Minnesota is committed to fostering local talent through employment opportunities. While this position utilizes a hybrid work modality
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UMR to ensure strategic coordination of development, internship, academic program, community event, and other types of collaborative activities with key partners. Navigate complex relationships and
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, Technology, Engineering, and Mathematics) domains and reading: scientific reasoning, technologies that support learning, mathematical problem solving, reading, and language comprehension. Quantitative Methods
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) • Expertise in studies involving intracranial glioblastoma xenograft models, genetically engineered murine glioblastoma models and patient-derived glioblastoma ex vivo models • Expertise in studies involving
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work with other trades, and prepare material requisitions. Plan, schedule, and monitor assigned project work including attending construction meetings, providing input to architects and engineers
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Qualifications: •A doctoral degree in a relevant field. "Relevant" is very broad. Scholars from neuroscience, biomedical engineering, psychology, physics, computer science, and many other disciplines have thrived
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-to-date instructions and assistance with technology in the Darland 4th floor conference room Collect and distribute AA staff mail from the UMD Mail Room (Darland basement) Submit work requests to Facilities
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at the intersection of systems neuroscience and computational modeling. Our lab is broadly interested in Bayesian inference, perception, multisensory integration, spatial navigation, sensorimotor loops, embodied