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postdoctoral researcher will leverage state-of-the-art protein language models (PLMs) and advanced AI-based structural modeling techniques to design and optimize T and B cell receptors (TCRs and BCRs). The work
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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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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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/CT and PET/MR imaging for cardiac applications. Responsibilities involve working with preclinical large animal models, preclinical and clinical PET imaging, image analysis, kinetic modeling, data
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based on NIH policy. They are also eligible for additional compensation in accordance with Yale institutional policy. Application Details: We would like to recruit a postdoctoral fellow in cancer outcomes
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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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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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. Experience working with rodent models is preferred but not required. The successful candidate should have excellent oral and written communication skill, be highly motivated for career development in
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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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cell and molecular biology in human cell models, cancer biology, and genomics. Experience in genomic instability, DNA damage/repair, and mutagenesis is beneficial. Computational experience is highly