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UCD Center for Labor and Community - Engaged Research Fellowship Project Coordinator (PROJECT POLICY
, trainings and other events as part of the Center’s California Worker Outreach Project initiative. This position will require extensive travel to priority northern counties in California to accomplish
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computer chips. Your role will be to design processes for transforming resources into sustainable materials by modeling reaction pathways from first principles. The project will collaborate with a broad
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cell sorting (FACS) or similar platforms. Experience using optical and/or electron microscopy to image biomaterials. Notes: Appointment Type: This is a full time, exempt from overtime pay (monthly paid
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processing, including HPC job orchestration with LLMs/agentic AI. Make spectroscopy actionable: Implement/benchmark modules for X‑ray, IR, and Raman; document assumptions; quantify sensitivity and uncertainty
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procedure cleaning and preparation of room for subsequent patients to ensure timely access to care. Assist surgeons; manage specimens; position patients safely on the operating table; perform general nursing
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documentation. Present research findings via oral presentations at scientific meetings, conferences, and research publications. What is Required: PhD degree in the Physical Sciences, Material Science, or related
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phenomena occur between the electrode and electrolyte. Perform advanced diagnostic studies to probe key phenomena and reactions occurring during battery operation, particularly the use of electron microscopic
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Job Summary Under the direction of the Director of the NSF Center for Pandemic Insights (NSF-CPI), the position is responsible for helping develop and deploy research technologies across the field
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architectures for science Developing and advancing extreme-scale scientific data management, analysis, and visualization Developing and advancing next-generation machine learning, AI, and data science approaches
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research into control theory of neural population dynamics. This position has the specific focus of developing ML methods to assess the feedback controllability of neural population dynamics recorded from