Bahram Parvin
Professor- Phone: (775) 682-6863
- Email: bparvin@unr.edu
- Building: WPEB
- Room: 329
- Mailstop: 0260
- Website: Dr. Parvin's Research Gate profile
- Pennington Cancer Institute, Renown Health, Senior Scientist, 2021-present
- University of Nevada, Reno, Professor of Cell and Molecular Biology, 2020-present
- University of Nevada, Reno, Director of Biomedical Engineering Program, 2015-present
- University of Nevada, Reno, Professor of Electrical and Biomedical Engineering, 2014-present
- Lawrence Berkeley National Laboratory (LBNL), CA, Principal Scientist, 1992-2015
- Ph.D., Electrical Engineering, University of Southern California, 1991
- Member of IEEE BISP Technical Committee (2019-present)
- Associate Editor of Organoids, an international, peer-reviewed, open access journal on all aspects of organoids published quarterly online by MDPI.
Research interests
My lab is developing (i) novel cancer therapeutics based on the normal signaling of the epithelial-stromal program and (ii) computational methods for identifying biomarkers of tumor heterogeneity.
Awards received
Parvin's Lab, at LBNL, received an R&D100 award in 2014 for the development of BioSig3D. BioSig3D is the first system for high content screening of 3D cell culture models.
Courses taught
- Bioimaging, Tissue Engineering, Deep Learning, and DSP
Prospective graduate students
There are open positions for highly motivated graduate students interested in cancer biology or bioimaging and machine learning.
- Cancer biology: Graduate students will investigate the mechanism of tumor suppression using cell-based assays, immunostaining, and OMIC data. There will also be future opportunities in drug delivery and animal studies. Applicants must have a background in molecular biology, biochemistry, or bioengineering. A B.S. in Engineering is not required.
- Bioimaging and machine learning: Graduate students will develop novel algorithms and software to identify biomarkers of tumor response based on multiplexed spatial and high dimensional discrete data. Applicants must have a master’s degree in computer science or engineering with solid programming skills in Python or related languages.
Interested applicants should email Dr. Bahram Parvin with the subject heading Prospective Graduate student (Cancer biology or Machine Learning) and include a CV outlining research interests, skills, and a list of references.