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team member to assist with the analysis of mass spectrometry data from cancer proteogenomics studies. This individual will contribute to the maintenance and development of existing computational tools
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to join the Cancer Computational and Systems Biology group. The Curtis Laboratory is administratively situated within the Stanford Cancer Institute and is integrated within Stanford University and the
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supervision of the Institute's Executive Director and Academic Program Director, in partnership with the Institute's faculty, fellows, and staff. The Tech Institute is a hub for policymakers, academics
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computational methods such as machine learning (ML), natural language processing (NLP), multi-modal large language model algorithms (LLMs), network analysis, and/or data mining to study the influence of digital
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needed to resolve foundational questions in quantum information science, and to guide near-term hardware and algorithm co-design. What You Will Do: Characterization of noise and errors (including non
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, virtual assistants, or AI-driven systems such as chatbots, recommender algorithms, or generative AI. The position focuses on how communicative processes are shaped by and shape these technologies
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include manage various datasets, estimate statistical models, report formats and other analysis considerations, determine and write statistical considerations and algorithms for protocol documents according
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of the Institute’s Executive Director and Academic Program Director, in partnership with the Institute’s faculty, fellows, and staff. The Tech Institute is a hub for policymakers, academics, advocates, and
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funding. KEY RESPONSIBILITIES A full-time Staff Associaate (Data Analyst II) for Molecular Medicine Learning Healthcare Program is needed to work under limited supervision of the Principal Investigators
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strong foundation in mathematics or computer science Familiarity with Python Interest in algorithmic game theory or machine learning theory. A combination of education and relevant experience from which