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standards. Report security, safety, equipment, or operational concerns promptly and accurately; complete required logs, reports, and documentation and maintain effective radio and face-to-face communications
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. What does our ideal teammate look like and what will you be doing? In this role, you will be responsible for working with subject matter experts to understand and refine new CFD application and/or CFD
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translation into energy, environment, and security solutions for the nation. What does our ideal teammate look like and what will you be doing? In this role, you will be responsible for working with subject
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translation into energy, environment, and security solutions for the nation. What does our ideal teammate look like and what will you be doing? In this role, you will be responsible for working with subject
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translation into energy, environment, and security solutions for the nation. What does our ideal teammate look like and what will you be doing? In this role, you will be responsible for working with subject
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Distinguished Staff Scientist (Cancer Biology and Radiopharmaceutical Therapy Development and Advanc
, proliferation, biomarker expression, and off-target effects. Integration of cancer biology with radiochemistry, isotope science, dosimetry, imaging, data analysis, and clinical collaborations to support
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characterization of polymers to maximize material performance but also close collaboration with multidisciplinary teams to scale up manufacturing processes for high-performance fibers. A key aspect involves
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and the business model (service delivery + research + partnerships), establishing operating practices, building the team, and engaging sponsors and users. You will be the face of the center internally
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SQL) or similar cloud tools OpenAI APIs, Microsoft Azure AI Foundry, Google Vertex AI and AWS Bedrock, Hugging Face, LangChain, GitHub, GitLab or other LLM frameworks Experience working with data models
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Experience using both: Cloud-hosted AI services (e.g., OpenAI, AWS Bedrock, Azure AI, Vertex AI, or similar) Locally deployed models (e.g., via Hugging Face, Ollama, vLLM, or similar) Familiarity with Model