Postdoctoral Position
at the LAWRENCE BERKELEY NATIONAL LAB,
IN QUANTITATIVE IMAGE AND STATISTICAL ANALYSIS OF BREAST TISSUE AT 
SUBCELLULAR RESOLUTION

The Knowles Lab (http://dwknowles.lbl.gov) is seeking a talented 
postdoctoral fellow in the area of quantitative image and statistical 
analysis to develop image-based methods to aid the early detection and 
sub classification of human mammary tumors.

This breast cancer project is a multidisciplinary effort between Life 
Sciences at LBNL, Basic Medical Sciences at Purdue, the Indiana Cancer 
Center, the Comprehensive Cancer Center at UCSF and the Institute for 
Data Analysis and Visualization at UC Davis. The goal is to link 
epigenetic organizational changes with in the nucleus with the phenotype 
or grade of normal, premalignant and malignant cultured and biopsied 
human mammary tissue. Working with 3D confocal images of human mammary 
tissue, the postdoctoral fellow will develop multidimensional features 
sets to describe the nuclear distribution of chromatin-related proteins 
at cellular resolution.

The applicant must have 1) a Ph.D. in computing science, biophysics, 
bioengineering or related field within the last four years; 2) 
Experience with single and multiphoton imaging techniques, 3) Expertise 
with C programming, linear systems, and advanced knowledge in image 
analysis techniques, 4) A demonstrated ability to conduct independent 
research as documented by a publication record. Experience with Matlab, 
the DIPimage toolbox, visualization techniques, bioinformatic 
techniques, cell biology and cancer biology would also be desirable.

This position is fully funded by a grant from the National Cancer Institute.

Applications to jobs.lbl.gov     
http://jobs.lbl.gov/LBNLCareers/details.asp?jid=20098&p=1