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Science, Electrical/Computer Engineering, or a related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with
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guidelines. Assist other lab members with experiments as required. May mentor research assistants and students With the assistance of the mentor, find and write research grants with the goal of obtaining
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. Anticipated Division of Time Research – 90% Mentoring – 10% Required Qualifications PhD in Animal Science, Environmental Science, Agronomy, Soil Science, Agricultural Engineering, or other relevant field
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experience using statistical software (e.g., R and Python) and AI tools (e.g., Claude Code) are a key requirement for the position. Successful candidates should show potential to excel in tasks related to meta
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., Microsoft Suite, Adobe Acrobat Reader, skills and creative use of technology to create efficient workflows and statistical databases) Supervisory Responsibilities No Required operation of university owned
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computational scientists, economists, engineers, and other researchers to develop data-driven, decision-relevant analytical tools for complex industrial systems. Key Responsibilities: Develop, improve, and apply
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 21 hours ago
of innovative technology solutions. Assignments will require technical and economic research involving data analysis, regulatory analysis, and modeling. You will learn by assisting with producing this research
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invasive in blood biomarker detection. In collaboration with our partners at the Karlsruhe Institute of Technology (KIT), you will develop data analysis pipelines as well as signal processing and inference
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Confidential Computing and Secure Multi-tenancy. The candidate will be able to make research contributions in areas of system software architectures to support secure computing enclaves on large scale HPC and
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in the world. This position is in the Technology Integration group within NCCS. Specific areas of research interest include: Telemetry collection and analysis to inform system optimization, workload