Senior Computational Biologist

3 weeks ago


San Francisco, California, United States UCSF Benioff Children's Hospitals Full time
Job Summary

We are seeking a highly skilled and experienced researcher to join our team at UCSF Benioff Children's Hospitals. As a Senior Computational Biologist, you will play a key role in developing innovative research programs in computational structural biology and leading the implementation of new therapeutic approaches.

Key Responsibilities
  • Lead the development of computational methods for analyzing protein structures and implementing innovative research programs in collaboration with faculty members and staff.
  • Conduct research, manage projects, and analyze results to advance the research agenda on various fronts simultaneously.
  • Provide guidance to graduate students and postdoctoral fellows in the laboratory setting and promote collaborative research between the Fraser laboratory and other faculty members.
  • Interact closely with faculty members and staff at UCSF and contribute to large national and international collaborative research projects.
Requirements
  • PhD in a related biomedical field with extensive experience in computational structural biology.
  • Strong understanding of protein structure and function, with experience in structural biology techniques such as X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy.
  • Experience working with government agencies or other national health and science-related agencies preferred.
  • Advanced communication and presentation experience preferred.
  • Experience with grant awards, scholarly publications, and international projects preferred.
What We Offer

UCSF Benioff Children's Hospitals is committed to diversity and excellence. We offer a competitive salary range of $83,300-$221,800 and a comprehensive benefits package. If you are a motivated and experienced researcher looking to contribute to our mission, please submit your application, including a CV, cover letter, and a two-page summary of past research and future goals.



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