930 phd-software-engineering-"https:"-"https:" Postdoctoral positions in United States
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simulations including mechanical engineering. As time permits, you will be encouraged to conduct your own independent research. Outstanding U of A benefits include health, dental, vision, and life insurance
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 6 hours ago
and graduate students Minimum Acceptable Education & Experience: PhD degree in Civil Engineering, Geography, or related fields Required Knowledge, Skills & Abilities: Proficient in geospatial data
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and/or Training: Bachelor's degree in biology or biomedical sciences Master's or PhD degree in Biology or Biomedical Sciences preferred Minimum Experience: 4+ years working in an academic research
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job-duties as assigned. Minimum Qualifications MD or Ph.D. in Basic Science, Health Science, or a related field. No experience required. Preferred Qualifications PhD in Epidemiology, Biostatistics, Data
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Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of physics—ideally in accelerator science or engineering—or a closely related field Demonstrated experience or strong interest
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physics (HEP) and nuclear physics (NP) experiments. The successful candidate will be a key member of a multidisciplinary co-design team integrating materials science, computing, and device engineering to
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Theory. Analyze large-scale educational datasets using statistical software such as R Support development of cognitive diagnostic assessments and item banks for introductory physics and calculus courses
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, and frequency noise measurements. Applicants should have a PhD in physics, electrical engineering, or related fields. US Citizenship is preferred. Interested candidates are encouraged to send a CV to
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reports and presentations for project sponsor. Minimum Qualifications: PhD in Mechanical Engineering required. Experience with hardware development and instrumentation required, as well as experience with
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Division of Time 80% Research: Build, train, and evaluate cutting-edge AI models and multi-agent systems for conservation genomics; perform feature engineering using chromosome-level genome assemblies. 15