Biology research experiences at Brandeis (Summer 2011)

Thanks to new funding from the National Science Foundation, starting in Summer 2011 Brandeis will offer a new research experiences for undergraduates (REU) program in Cell and Molecular Visualization. This new grant, organized by principal investigator Susan Lovett, will provide funding for 10 undergraduates to spend 10 weeks at Brandeis in the summer doing independent research projects in close collaboration with faculty mentors. NSF REU programs place special emphasis on providing research opportunities for under-represented groups in science, and for students whose colleges cannot provide cutting-edge research facilities.

The new program will join Brandeis’s  existing MRSEC REU and other summer research activities in providing a lively atmosphere for young researchers. This competitive program will provide stipends of $5000 each plus housing and meal allowances. Participants must be US citizens or permanent residents, and should have completed their sophomore or junior year of study and be enrolled in an accredited undergraduate college or university. Further information including an application form is available on the Biology website.

Being given the opportunity to do research as an undergrad was amazing, fun, intellectual, and extremely useful; I’ve done it for two summers now.   At the beginning of my college career I was pre-med, but it only took a summer of research to help me realize that I actually want to do science over the course of my career […]

(see more quotes from undergraduates about summer research)

New for Spring 2011: CS177 Scientific Computing

The Computer Science department will be offering a new course this semester, CS177 Introduction to Scientific Computing, taught by Prof. Tim Hickey.  The course has no prerequisites and is designed for Science students interested in learning how to use Matlab and other tools to analyze data and simulate physical systems. It meets MWT 9-10 and there is still room for more students. The first part of the course will be an introduction to the lingua franca of the Scientific programming community:  Matlab/Octave. No programming background is assumed or required. The second part of the course will cover the use of Matlab/Octave to solve a variety of scientific problems using various techniques including statistical analysis, curve fitting, optimization, ordinary and partial differential equation solving, image processing, SVD and other matrix factorizations, 2d and 3d plotting. Students will also learn to use  a number of tools for collaboration and dissemination of scientific results including LaTeX for scientific papers, GIT for source code sharing, google docs for shared editing and google sites for dissemination of results. For more info see the course website

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