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Field
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directly into their DNA. The lab combines experimental and computational approaches to develop and apply barcode-based lineage recording systems, single-cell technologies, and perturbation tools to uncover
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is part of the Prostate Cancer Program and is located next to the Nelson Lab (https://research.fredhutch.org/peternelson/en.html) and the Haffner lab (https://research.fredhutch.org/haffner/en.html
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Postdoctoral Research Associate - Training in Pediatric Cancer Survivorship Outcomes and Interventio
training grant from the National Cancer Institute or our institutional budget. Applicants to positions funded by the T32 training grant must be citizens or noncitizen nationals of the United States or have
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will test the ability of known and near-clinical drugs to reverse or block these changes and ultimately aims to develop a preventive breast cancer vaccine for individuals with inherited predisposition
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apply those discoveries to develop more effective approaches to cancer prevention, diagnosis, and therapies – providing tomorrow’s standard of care today. A Cancer-Free World Begins Here. The OSUCCC
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interested in gaining training and experience in environmental epidemiology and cancer epidemiology. The primary objectives focus on climate sensitivity hazards and cancer-related health outcomes. However
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literacy with at least basic programming skills (R, Python). Analytical mindset, with a keen interest in advancing proteomic methodologies Knowledge of cancer biology is an advantage We offer Cutting-edge
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Zheng, and other collaborators to develop statistical and machine learning methods for medical decision-making in cancer prevention and early detection. Key areas of focus include, but are not limited
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underlying cancer treatment resistance and the development of new therapeutics. The training will be mentored by Dr. Michael Haffner and members of his research group. Training opportunities are provided
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language models (LLMs), generative AI, and cancer informatics. Projects may include training and fine-tuning domain-specific LLMs for clinical document summarization, treatment recommendation reasoning