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protein foods including through high moisture extrusion. Key responsibilities will include: Explore innovative methods for food process optimization including the use of AI and machine-learning Develop and
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Collaborate with domain experts to integrate LLM-based solutions into predictive maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance
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and e-commerce marketing with a high-volume promotions calendar Improving digital commerce performance through testing, optimization and performance reporting Managing paid media campaigns and budgets
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project aimed at advancing our single-cell ribosome profiling technologies in cancer. For further information about the lab, please visit https://www.sendoellab.org/. The Institute for Regenerative Medicine
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the coding and coding denial teams. This position ensures accurate and compliant coding practices to optimize revenue capture and oversees the follow-up and resolution of coding-related denials and appeals. By
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the reasoning and code-generation capabilities of LLMs and SLMs. The research will design autonomous agentic workflows to tackle complex networking challenges, including real-time network optimization, protocol
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: Maintain I-9 compliance Apply all university and department policies, procedures and legal requirements Maintain file security and hazard protection Process public record requests Optimize client and program
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related content in partnership with instructors and program staff. Manage course content within the Salesforce-based system, ensuring accuracy, completeness, and readiness for publication, while optimizing
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various experiments taking place in the laboratory, including: - Optimize and perform in vivo and ex vivo imaging experiments - Optimize and perform behavioral experiments - Maintain animal colony - Rodent
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optimally for future challenges. This PhD position is part of the SecReSy4You MSCA Doctoral Network, which focuses on developing next-generation methods for security and resilience of cyber-physical systems