Stanford Biomedical Data Science Program

Stanford Biomedical Data Science Program

高等教育

Stanford，CA 1,340 位关注者

PhD and MS program in the Department of Biomedical Data Science at Stanford University

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关于我们

The Stanford Biomedical Data Science Program is a graduate and postdoctoral training program within the Department of Biomedical Data Science at Stanford University School of Medicine. Our mission is to train future research leaders to design and implement novel quantitative and computational methods that solve challenging problems across the entire spectrum of biology and medicine. The program is flexible, and attracts applicants with training in biology, research and clinical medicine, computer science, data science and analytics, statistics, engineering and related disciplines. We are home programs in the School of Medicine's Biosciences Programs. We have an active diversity recruitment program, and strongly encourage applications from traditionally underrepresented minorities, those from disadvantaged backgrounds, and those with disabilities. We also offer an ACGME-accredited Clinical Informatics Fellowship program at Stanford, as well as a distance MS program for working professionals, and online informatics courses and a certificate program in Biomedical Informatics. Sylvia Plevritis, PhD – Professor and Chair, Department of Biomedical Data Science Research and graduate education in bioinformatics; clinical/biomedical/imaging informatics. We offer a PhD, and three masters degree programs (research, distance-learning, and a co-terminal degree for Stanford undergraduates).

网站
https://dbds.stanford.edu/
所属行业
高等教育
规模
51-200 人
总部
Stanford，CA
类型
教育机构
创立
1982
领域
bioinformatics、clinical informatics、medical informatics和imaging informatics

地点

  • 主要

    Stanford University School of Medicine

    1265 Welch Road, MSOB X 343

    US，CA，Stanford，94305-5464

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Stanford Biomedical Data Science Program员工

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动态

  • This posting is from Professor Julia Salzman: We are an exciting and disruptive start-up in life sciences and artificial intelligence. We aim to develop a foundation model trained on a new scale of biological data, leveraging recent scientific discoveries published in high impact journals. We anticipate that this model will have broad applications across the life sciences, including drug discovery, molecular engineering, diagnostics, and therapeutics in many disease-relevant domains and have several go to market strategies. We are seeking for several experienced and highly motivated machine learning software engineers and research scientists to architect and scale up the foundation model. The ideal candidates will be versatile in modern deep learning architectures and, desirably, data science. We offer competitive salaries and generous benefits, as well as a generous equity program for employees. Please send a cover letter and CV to?[email protected]?. Qualifications:? BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) 5+ years of hands-on experience, primarily with Machine Learning and Deep Learning software architecture and frameworks Strong programming skills, especially in Python and C Strong problem-solving and debugging skills Excellent knowledge of theory and practice of Generative AI and large and scalable machine learning models Excellent presentation, communication and collaboration skills Desire to be involved in multiple diverse and creative projects Backgrounds and keen interests in bioinformatics/genomics/proteomics/drug discovery etc. are highly desirable.?

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