Computational Biology

Options

Volunteer Basis, Potential for UROP Funding, Potential for Work-Study Funding, Potential for Academic Credit

Overview

Spatial omics analysis and software engineering

The Dries lab (www.drieslab.com) provides a multi-disciplinary research environment that focuses on bringing cutting-edge technologies and computational tools to the forefront of biomedical and clinical research. We are specialized and worldwide leaders in the emerging field of spatial multi-omics research, which provides unique molecular (RNA, protein, metabolome, …) information at the single-cell and subcellular level within intact tissues. In this manner we don’t only focus on the role of individual cells, but also how multiple cells coordinate their functions and interact to drive biological processes in both health and disease. Together, this approach creates the next wave of big data for which we develop innovative approaches to better understand and predict how tumors will respond to treatment or to identify potential novel vulnerabilities. In this role we are developing and maintaining an open-source software tool called Giotto Suite (www.giottosuite.com). Giotto Suite is a technology-agnostic framework that facilitates the analysis of expression and spatial data at multilevel resolutions, streamlining annotation and visualization of spatial multi-omics data. The candidate will be given the opportunity to work at the crossroads of research software engineering, method development and data analysis with a strong focus on translational oncology work. They will begin with integrating the high-end imaging and visualization platform Napari (https://napari.org/dev/index.html) into Giotto Suite and will leverage novel machine learning techniques on large -omics datasets. We are specifically interested in students willing to work in a collaborative environment and at the forefront of open-source software development.

The optimal candidate has experience or enthusiasm for:
Python
Package development and maintenance
Machine learning and artificial intelligence algorithm development
GitHub, or similar version control system
C/C++ (plus)
R (plus)

This position will require 5-10 hours per week, and will continue through the academic year. Direct mentorship by a lab member is plausible. Contact Ruben Dries at rdries@bu.edu with any questions or your resume/CV to apply.

Back to On-Campus Opportunities