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streamline processes, reduce handoffs, and improve agent efficiency. Contributes to the development and maintenance of knowledge articles, job aids, and training content based on recurring Tier 2 issues
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, and improve agent efficiency. Contributes to the development and maintenance of knowledge articles, job aids, and training content based on recurring Tier 2 issues. Reporting & Continuous Improvement
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areas of the brain. Treatment is based on rapid delivery of the thrombolytic agent (t-PA), but the delivery of the drug is limited by the obstruction of the vessels. In this project, the post-doctoral
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to identify user needs and requirements for efficient, scalable and reliable data pipelines and models that support data-driven initiatives. Support automation of operational workflows using Agentic AI
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Python, PyTorch, and Linux/command line Familiarity with LLM in-context learning and prompt engineering Basic understanding of modern LLM models, ecosystems, and pipelines, including retrieval-augmented
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code comments and appropriate documentation to various knowledge-based system(s) to simplify code maintenance and to improve the support. Testing & Documentation Create and document test scenarios using
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-Machine Interaction Software Development AI Agents Physics-informed Machine Learning Diffusion Models Synthetic Data Digital Twins Application Domains We also value experience applying AI in fields such as
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. This should include a description of a deep learning project that you have executed, ideally a creative use of a transformer-based or related architecture that you trained yourself. If it is in the sequence
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. Students will develop familiarity with both model-based and model-free reinforcement learning algorithms, including Q-learning, Actor-Critic algorithms, and multi-armed bandit algorithms. More information
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, systems, and hardware design. Experience in one or more of: LLMs, AI agents, embedded ML, physical modelling and simulation Strong programming skills in Python and C/C++, familiarity with ML deployment