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test the hypothesis that the targeting of multiple mutations will enhance survival in glioblastoma. We propose to identify an amino acid substitution that can enhance proteasome processing followed by
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the design and development of multiple projects using state-of-the-art AI models, algorithms, statistical models, and other programs designed to improve the public sector. Work with large untapped data
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data-driven departmental budget, goals, and objectives in alignment with organizational goals. Develop strategic department plans, policies, and procedures for alumni programs and events that enhance
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computational biology workflows; statistical methods in data analysis, with applications to high-throughput sequencing or other biological assays; fundamentals of software engineering; strong knowledge
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Program at the Stanford Cancer Institute. She has an academic interest in Precision Medicine and her lab applies cutting-edge sequencing and imaging technologies to better understand skin cancer and rare
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experience. Desired skills: Gene and single cell analytics experience, behavioral tests, hiPSC cell culture, stem cell differentiation, hiPSC-derivative transplant, RNA Sequencing, viral approaches, and
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(Spiegel et al. Nat Med 2021, Majzner et al. Nature 2022, Frank et al. Lancet 2024). We have generated a wealth of single-cell sequencing, spatial, clinical, and other types of data from these and other
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screening platform. Work together with team members in the construction and sequencing of single-cell transcriptomic and epigenetic libraries. Conduct lab experiments involving isolation and culture of immune
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Key Responsibilities: • Adapt internal computational pipelines to analyze high-dimensional patient datasets, including single-cell sequencing, spatial transcriptomics, clinical, and other relevant
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technologies for probing protein-RNA interactions at scale. Our laboratory aims to solve the fundamental challenge of predicting protein-RNA complex structures directly from sequence by integrating high