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                agents based on reinforcement learning with open-source LLMs or VLMs. Required skills include extensive experience with LLM post-training, including Supervised Fine-Tuning (SFT), Low-Rank Adaptation (LoRA 
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                receive stipend support and may request training related expenses based on NIH policy . They are also eligible for additional compensation in accordance with Yale institutional policy . Application Details 
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                postdoctoral position at the interface of decision analytic modeling, pharmacoepidemiology and clinical hematology-oncology within the Section of Medical Oncology and Hematology, Department of Internal Medicine 
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                . Studies incorporate approaches in both primary human immune cells and in vivo mouse intestinal model systems. Education and experience: Candidates must have a PhD or equivalent degree with a strong 
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                , families), conduct school-based research, and maintain school relations Excellent statistics skills, including experience with longitudinal data analysis and multi-level modeling Excellent communication 
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                highly motivated to impact patient outcomes through translational approaches to the treatment of T cell malignancies. Experience with in vivo mouse immunotherapy models, protein/antibody engineering and 
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                positions) in the areas of privacy-preserving health data sharing, AI modeling and evaluation of medical and biological applications. The Postdoctoral Associate will be responsible for co-developing and 
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                ), genome/phenotype analysis (Dr. Jihoon Kim) and applications of large language models (Dr. Ohno-Machado). The Postdoctoral Associate will be responsible for co-developing and conducting research projects 
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                are invited for a Postdoctoral Associate to join the research group of Dr Sarah Aitken (MBChB PhD) in the Center of Molecular and Cellular Oncology, Yale Cancer Center investigating the causes and consequences 
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                driven individual with a PhD in data science, computer science, biomedical informatics, or a similar background with some experience working with large datasets. Prior experience with healthcare is not