We are now looking for highly-motivated candidates for multiple positions including Post-doctoral Research Fellows or Research Associates, Imaging Analysts and Software Engineers. The research projects include:
1. Develop structural, functional and diffusion MRI prognostic biomarkers and machine learning models of early detection/prediction of neurodevelopmental deficits and other important clinical outcomes for high risk newborns and infants;
2. Develop machine learning/deep learning methods using conventional MRI and MR elastography data to accurately detect and quantify liver fibrosis, using biopsy-derived histologic data as the reference standard;
3. Large-scale collaborative analyses of radiomics and genomics data for prediction/diagnosis neurodevelopmental disorder or liver, bowel other disease prediction;
4. Develop machine learning/deep learning algorithms for MRI image reconstruction.
A Bachelors, MS or PhD degree in computer science, mathematics, biomedical engineering, bioinformatics, electrical engineering, physics or related field.
Strong programming skills with Python, Matlab.
Strong communication skills in written and verbal English. Trackable publication records.
Extensive experience in machine learning and deep learning development with Scikit-learn, Deep learning package (e.g., Tensorflow, Keras), and Matlab packages.
MRI image research experience is a plus.
Applicants should email a CV, along with a brief letter outlining their research background and interests to Dr. Lili He: firstname.lastname@example.org