Research Fellow in Medical Image Analysis and Machine Learning

This position has been filled. Thanks for your interest.

Departments of Pediatrics and Radiology at Boston Children’s Hospital and Harvard Medical School invite applicants for the open positions at the postdoctoral research fellow and graduate research assistant levels.

The funded project involves collaboration radiologists, radiation oncologist, neuroscientists, neonatologists, pediatricians, neurologists and psychiatrists. The projects involve developing and using medical image analysis and machine learning algorithms to quantify normal neurocognitive development, to understand the mechanisms and to predict adverse neurocognitive outcomes in patients undergoing treatment for brain lesions at various childhood stages.

The successful candidates will be in the final years of PhD or have a PhD degree in the BME, EE, CS, Applied Maths, psychiatry, neuroscience or related fields. Experience in machine learning and medical image analysis is preferred but not required.

Visiting scholars from related fields are welcome.

The new members will be working closely with Dr. Yangming Ou, a junior faculty in the Fetal-Neonatal Neuroimaging Data Science Center at BCH. Dr. Ou’s team is also affiliated with BCH’s Computational Health Informatics Program. Members in the team (postdoc fellows, PhD students, and research assistants) work on MRI analysis and machine learning for abnormality detection, early screening of disorders, outcome prediction, treatment evaluation, as well as neuroimaging biomarkers for typical and atypical brain development.

Interested applicants can send the CV to Dr. Yangming Ou at yangming.ou@childrens.harvard.edu.

Boston Children’s Hospital and Harvard Medical School is an equal employer. Applications will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy, and pregnancy-related conditions or any other characteristic protected by law. Under-represented groups in STEM are especially encouraged to apply.