633 structural-engineering-"https:"-"https:"-"https:"-"https:" positions at Nature Careers
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Job Description St. Jude Children's Research Hospital's Department of Imaging Sciences is a new academic department that is recruiting faculty-level scientists and engineers specializing in
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Ability to work in a team Desirable qualifications are: Teaching experience / experience of working with e-learning Knowledge of university processes and structures Basic experience in academic research
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$50,852.80 (minimum) - $63,566.00 (midpoint) - $82,635.80 (maximum) Please note: this range is pro-rated for part-time, 20 hours per week. Pay Type: Annual HHMI’s salary structure is developed based
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. #LI-BG1 Compensation Range $18.00 (minimum) - $24.90 (maximum) Pay Type: Hourly HHMI’s salary structure is developed based on relevant job market data. HHMI considers a candidate's education, previous
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structures or animal behaviors. The PTR-Bioimage Analysis team within Project Technical Resources (PTR) collaborates with the AI@HHMI initiative, Team Projects, and Janelia laboratories to provide ground
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abroad) Physical conditions for participating in research flights Driver's license Knowledge of university processes and structures What we offer: Exceptional projects, outstnading resources and
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and technology. The foundation is particularly interested in U.S.-based projects consisting of diverse teams of scientists, practitioners, and key stakeholders (e.g., community members, landowners
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of Science in AI, with two distinct streams: Business and Engineering, and are looking for passionate and highly motivated Teaching Faculty. The Undergraduate Division is seeking teaching faculty in
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Engineering or a related field The ideal candidate should have some knowledge and experience in the following topics: Software Cybersecurity Software Testing and Analysis Machine Learning and Multimodal Large
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, or autonomous driving applications Perception and Sensor Fusion: Strong background in processing and fusing data from cameras, LiDAR, radar, or other sensors for robust autonomous system perception ML Engineering