Postdoctoral Associate Opportunities at Duke Vision and Image Processing Laboratory
Immediate opening at Duke University Biomedical Engineering Department for a postdoc interested in interdisciplinary applications of image analysis and computer vision with emphasis on applications in medical imaging.
NOTE: Applicants are encouraged to submit their application as soon as possible.
Postdoc will be supervised by Prof. Sina Farsiu (http://people.duke.edu/~sf59/ ) .The candidate must have a demonstrated strong background in image processing as evidenced by publication of papers in high-impact peer-reviewed journals. Programming skill in MATLAB/Python is required. GPU, C++, or mobile app programming experience is a plus but not mandatory.
PhD in EE, BME, or CS. Experience in ophthalmic sciences, optical coherence tomography, adaptive optics is desired but not necessary. Projects can be chosen based on the interests and background of the individual candidate. The position will remain open until filled. The position will remain open until filled. Interested candidates should submit their CV in PDF format including link to Google Scholar webpage.
Duke is committed to encouraging and sustaining work and learning environments that are free from harassment and prohibited discrimination. Duke prohibits discrimination and harassment in the administration of both its employment and educational policies. Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, genetic information, gender, gender expression, gender identity, national origin, race, religion, sex, sexual orientation, or veteran status. Duke also makes good faith efforts to recruit, hire, and promote qualified women, minorities, individuals with disabilities, and veterans.
Duke is an Affirmative Action / Equal Opportunity Employer committed to providing employment opportunity without regard to an individual’s age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status. |