Postdoctoral Researcher in Machine Learning and Biology

4 days ago


Palo Alto, California, United States Stanford University Full time
Postdoctoral Scholar in Machine Learning and Biology

We are seeking a highly motivated postdoctoral scholar to join our machine learning group at Stanford University School of Medicine. As a postdoctoral scholar, you will have the opportunity to work with our team of world-experts in artificial intelligence, biology, and medicine to develop innovative solutions for real-world problems.

Our research focuses on integrating machine learning with clinical data to improve patient outcomes. We are particularly interested in exploring the intersection of machine learning and medicine, and we are looking for a scholar who is passionate about this area.

As a postdoctoral scholar, you will have the opportunity to work on a wide range of projects, from developing new machine learning algorithms to applying existing techniques to real-world problems. You will also have the opportunity to collaborate with our team of researchers and clinicians to translate research findings into actionable insights and products.

We are committed to diversity and inclusion, and we encourage applicants from underrepresented groups to apply. If you are a highly motivated and talented individual who is passionate about machine learning and medicine, we encourage you to apply for this exciting opportunity.

Responsibilities
  • Develop and apply machine learning algorithms to clinical data
  • Collaborate with our team of researchers and clinicians to translate research findings into actionable insights and products
  • Contribute to the development of new machine learning techniques and tools
  • Present research findings at conferences and workshops
Requirements
  • PhD in a quantitative field with research experience in machine learning
  • Excellent publication and external funding track record
  • Interest in medicine and biology
  • Familiarity with modern AI/ML platforms and libraries
Preferred Qualifications
  • History of publications in leading AI/ML/Bioinformatics conferences and journals
  • Diverse experience in varied AI/ML concepts
  • Track record in development of open-source software adopted by the research community
  • Experience in medicine and/or biology
Keywords

Machine Learning, Data Science, Deep Learning, Multitask Learning, Transfer Learning, Representation Learning, Graph Learning, Foundation Models, Clustering, Classification, Data Visualization, R, Python, Julia, Bioinformatics, Systems Biology, Immunology, Single Cell Analysis, Multiomics, Integrative Analysis, Medicine, Single Cell Biology, Cytometry, Flow Cytometry, Mass Cytometry, Proteomics, Metabolomics, Genomics, Sequencing, Human Activity Monitoring, Actigraphy, Pregnancy, Trauma, Surgery, Stroke, Precision Medicine, Personalized Medicine, EHR, Electronic Health Records, Wearable Devices



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