Biology

Assistant Professor of Biology

The Department of Biology at the University of Richmond invites applications for a tenure track position as an Assistant Professor of Biology. The start date is August 2019. We seek a broadly-trained biologist who will excel in inclusive, undergraduate teaching and engage undergraduate students in their productive research program. Candidates should have a doctoral degree, postdoctoral experience, and expertise in the field(s) of ecology, evolution, or organismal biology.

Physician-Scientist (Assistant/Associate Professor) - Stanford ChEMH

Stanford ChEM-H is an independent institute at Stanford University, formed in partnership with the Schools of Medicine, Humanities and Sciences, and Engineering. More information about the institute can be found on chemh.stanford.edu/. The Institute is seeking applicants for a University Tenure Line faculty position at the junior level (Assistant or untenured Associate Professor). Applicants are expected to have earned an M.D./Ph.D. degree and be board certified or eligible in any medical specialty.

Assistant/Associate Professor – Stanford ChEM-H

Stanford ChEM-H is an independent institute at Stanford University, formed in partnership with the Schools of Medicine, Humanities and Sciences, and Engineering. More information about the institute can be found on chemh.stanford.edu/. The Institute is seeking applicants for a tenure-track faculty position at the junior level (Assistant or untenured Associate Professor). Applicants are expected to have earned a Ph.D. or M.D. degree in any discipline of science, engineering or medicine.

Big Data Image Processing & Analysis Workshop Course

University of California, Irvine's Center for Complex Biological Systems is pleased to announce the annual short course in Big Data Image Processing & Analysis (BigDIPA), September 17-21, 2018.

This 1-week workshop course is geared towards graduate students, postdocs, faculty and industry professionals with research interests in navigating, manipulating and extracting information from "Big Data" image sources. The course is designed to cover the complete "vertical integration" of the image data to knowledge pipeline.