Student Research Opportunities in the CSS Biocomputing Lab
The UWB CSS Biocomputing Laboratory is interested in the intersection of biology and computing. This includes building simulations of biological systems, developing computational solutions for biology, analyzing simulation or experimental data, and developing all of the infrastructure necessary to do these things and disseminate our results. This means that we have a wide range of opportunities for students to help, from new CSS majors to graduate students searching for a thesis topic. It also means that our work intersects with a number of CSS faculty members' interests, as well as colleagues in other UWB programs and at other campuses. If you're interested, you can begin working in the lab early in your career here at UWB doing general tasks and learning about the specifics of our work, and later start on more ambitious projects. This is an excellent way to build a portfolio of work and to build professional connections with faculty and other students.
- Documentation (work with faculty and more senior students to build an understanding of what we've done and how our software works).
- Dissemination and web (learn about what we do by explaining it to others).
- Data analysis and visualization (apply general programming skills and/or mathematical background to process and present up to terabytes of data).
- Software engineering (apply what you've learned about SE to help bring order to the chaos of experimental software, help verify that our software does what we think it does, etc).
- Simulation (help to develop and expand simulations of brain growth and function).
- GPGPU algorithm development and programming (learn to move single-threaded code to graphics processing units; optimize code to gain maximal speedup on GPU architectures).
- Multicore programming (learn how to speed simulation and analysis software up by using more than one CPU core).
- Distributed programming (speed up data analysis by distributing tasks across multiple computers).
- Big data (some of our simulations could, in principle, generate terabytes of data; how can we handle this?).
- Software Engineering (develop reusable tools to help biologists and computational scientists move their projects to GPUs, etc).
- Masters projects and theses (these specialized topics contain the seeds of a number of excellent MS projects and theses).