Postdoc research on imaging genomics with machine learning at Tulane University

Several post-doctoral fellow or PhD graduate research assistant positions are available immediately to work on the development of machine learning, image processing, statistical and signal processing approaches for the analysis and integration of genomic and medical imaging data. More information about our research work at Multiscale Bioimaging and Bioinformatics Laboratory of Tulane Biomedical Engineering Department can be found at our website (http://www.tulane.edu/~wyp/). The position will be funded by both NIH and NSF. The candidate will have a chance to collaborate with people at Tulane School of Sciences and Engineering, School of Public Health and Tropic Medicine and School of Medicine. Tulane is a private university and a member of the 63 prestigious Association of American Universities (AAU). Tulane is ranked as the 39th best national university in 2016 by US News Report, providing a unique environment for learning and research. The salary for post-doctoral fellow is negotiable, commensurate with the experiences of the candidate.
Qualifications:
(1) A degree in Applied and Computational Mathematics, Biomedical Engineering, Electrical Engineering, Computer Science, Statistics or other related fields; (2) Programming skills with MATLAB or C; (3) Experience and knowledge of signal processing, machine learning and statistical analysis; (4) Knowledge of biology and genomics is desirable but not required.
Contact:
Yu-Ping Wang, PhD
Professor of Biomedical Engineering, Computer Science, Neuroscience,
& Department of Biostatistics and Bioinformatics
Tulane University
500 Lindy Boggs Bldg. New Orleans, LA 70118
To apply for the position, please send CV with a list of three references to wyp-AT-tulane.edu