OCIO Machine Learning Postdoctoral Fellowship


Open fellowships will be announced at https://datascience.si.edu/opportunities.

The OCIO Data Science Lab was formed in response to the dramatic increase in all forms of digital data across the Smithsonian. We seek to build collaborations both across Smithsonian units, as well as universities and other institutions. Members of our group work on a variety of data-intensive research topics including biodiversity genomics and machine learning applications of digitized museum collections and archives. See a list of our recent publications here: https://datascience.si.edu/data-science-lab-publications. Fellows may design their own project or choose to build off of our current projects and collaborations. They will have the opportunity to become a certified Carpentries instructor and teach data science skills as part of our training program for Smithsonian staff, fellows, and interns (https://datascience.si.edu/carpentries) if desired.


Given the interdisciplinary nature of the Data Science Lab and the potential for collaborations across the Smithsonian, applicants should possess a Ph.D. with a relevant interdisciplinary focus. This may include either biological sciences, social sciences, or humanities disciplines with a research focus in digital data or technical disciplines (e.g., computer science, NLP) with a research focus on historical data. Strong written and communication skills are also required. Applicants should be proficient in Python and familiar with deep learning libraries such as PyTorch or TensorFlow. Open fellowships will be announced at https://datascience.si.edu/opportunities.


One year, with the potential to renew for an additional year.


$60,000, plus $5,000 for health insurance and a $5,000 research allowance.


Rebecca Dikow



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