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Research Fellow - DLMP - Han lab

Job Description - Research Fellow - DLMP - Han lab

Description

The Research Fellow will work on new and ongoing projects in the Division of Computational Pathology and Artificial Intelligence. Projects will provide an excellent opportunity to work with multidisciplinary teams and large clinical data sets. 

Mayo Clinic has embarked on digitizing its large collection of glass slides, with several million gigapixel images currently available. The research fellow will use these data sets, accompanied by other clinically sourced data, as a springboard to pursue multiple cutting-edge topics in machine learning, image analysis, and discovery in support of the clinical and research activities of the division. The fellow will work on projects that include:
 

  • Developing novel algorithms to classify, segment, characterize, or predict patient outcomes, biomarker status, or disease
  • Evaluating model behavior and robustness, with a focus on developing novel methods to improve model performance and generalizability 
  • Analyzing human-AI interaction to understand the human factors associated with AI augmentation of pathology
     

The research fellow will work under the mentorship of pathologists and data scientists, and will work closely with other trainees, IT groups, and other staff in support of these projects.

A Research Fellow at Mayo Clinic is a temporary position intended to provide training and education in research. Individuals will train in the research program of a Mayo Clinic principal investigator. Qualified individuals will demonstrate the potential for research as evidenced by their training and peer-reviewed publications and should become competitive for national research grants. Proof of English proficiency is required for J-1 Short-Term Scholars, Research Scholars, Professors, Specialists, and Student Interns sponsored by Mayo Clinic.
 

 

 



Qualifications

Must have a Ph.D., M.D., or equivalent doctoral degree in a field deemed relevant by the program.

 



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