Research Assistant - Deep learning for biological imaging data analysis

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Sponsoring College, Department, School or Center: 
Center for Biological Physics & Department of Physics
Faculty Name: 
Douglas Shepherd
Preferred Skills or Majors: 

A background in any science, engineering, or mathematics field is appropriate. The position will learn and apply computational, practical programming, and mathematic skills to solve the research problem. The ability to work independently is critical. Course credit, work-study, or employment for at least 10 hours per week are possible following a semester of productive work on the project.

Closing Date: 
September 30, 2019
Location or Campus: 
Hours Per Week: 

Desired Academic Year: 
Project Description: 

The Quantitative Imaging and Inference (QI2) lab, directed by Dr. Shepherd, is looking for a highly motivated undergraduate to contribute to the Chan Zuckerberg Initiative Human Cell Atlas project. We are part of the newly formed network to create an atlas of cells within the human lung. This position is a good fit for someone interested in 1) deep learning for image processing, 2) how to work with big data, or 3) how multiple types of biological data can be combined to create new knowledge. This position will help develop computational tools to integrate results from RNA sequencing and 3D imaging of human tissue. The trainee will receive close mentorship on all aspects of the project, along with the freedom to steer the project if they choose.

Application Instructions and Contact Info: 

Email a resume/cv, including relevant courses/experience, and a brief note about why this project interests you to Dr. Douglas Shepherd ( Include the words ‘HCA-honors-ad’ in the subject heading. Informal inquiries are welcome.