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reinforcement learning for large language models (LLMs). Research directions include developing next-generation post-training algorithms, exploring diffusion-based approaches to reasoning with language models
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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
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. Additionally, the impact of chemotherapeutic agents on cardiac tissue function will be studied using this model. Goals Identify appropriate scaffold base materials, evaluate various crosslinking methods (such as
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