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Postdoctoral Fellow Job Listing

The Scientific Image Analysis Group (SIAG) is a new effort at Harvard to create, develop, and implement advanced algorithms that facilitate science with images, and share them with the world. To facilitate these advances, the SIAG seeks a talented, promising, and diverse group of researchers at an early career stage to join the SIAG Fellowship program. The role of a SIAG Fellow is to spark vital interdisciplinary collaborations across the primary SIAG focus areas of astronomy, bioimaging, and remote sensing. Such collaborations have the power to generate new ideas and approaches across disciplines, to abstract image analysis challenges beyond their native domains to inform the development of cutting-edge tools, and to instill a common language across disciplines. Our program aims to appoint up to three new postdoctoral SIAG Fellows next year, each for a three-year fellowship term. Fellows will spend most of their time on SIAG Key Projects, having the opportunity to spend 20% of their time on individually led research projects. Fellows will have access to the Harvard Cannon cluster, with 100,000 CPU cores and hundreds of GPUs. 

Fellows will be selected through an annual application process. Applicants should have, or be expected to receive by the 1st of September 2023, a PhD in Physics, Statistics, Computer Science, or a related field.  

Complete applications must include: 

  • Cover letter (no more than 1 page)

  • Curriculum Vitae (1-2 pages recommended, but longer accepted) 

  • Statement of research interests (no more than 2 pages) 

  • List of publications 

  • Name, title/Institution, and contact details for three professional references 

The deadline to receive all the materials is Monday, January 30, 2023.

Please send all materials to SIAG@fas.harvard.edu. 

Harvard is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status.