Design of quantitative image analysis tools for single-cell biology
Amy Herr, Professor
Bioengineering
Closed. This professor is continuing with Fall 2023 apprentices on this project; no new apprentices needed for Spring 2024.
Imaging data forms the backbone of modern bioengineering research. Analysis of imaging data benefits from creative, methodical algorithm design, rigorous validation, and water-tight documentation and training of users. The student will work independently, in a self-directed but supervised manner to design, develop, validate, and deploy an image processing algorithm for the automated detection and characterization of microscopic features in fluorescence and brightfield micrographs. The student will work with Bioengineering graduate students in understanding the unmet data analysis needs of single-cell quantitative analysis, and will become proficient in the project background as well as the specific design requirements for the software tool.
Role: In this role, the selected candidate will receive one-on-one mentoring from a PhD student in Bioengineering and interfacing with a faculty member. For the first phase of the project, the student will have a focused set of responsibilities working as a programmer. The student will learn about scientific image analysis, design and application of rigorous image analysis pipelines (e.g., Matlab, ImageJ, Python), best practices in documentation and reproducibility/replicability, and team and individual communication.
The student will join for weekly lab group meeting and research team meetings, as well as social/community-building functions.
If performance is outstanding, the selected candidate will be invited to continue in the research role
Qualifications: We are recruiting junior and senior year undergraduate students with proficiencies in matlab, python, or other programming software/languages sufficient for image processing. The student should also have proficiency in statistical analysis and data presentation. The ideal candidate should be versatile and excellent at communicating in both written and oral formats. An innovation mindset and desire for excellence in execution of projects are sought. Any computer science or engineering major is suitable, so long as the mentioned proficiencies are met.
Day-to-day supervisor for this project: Maya Overton, Ph.D. candidate
Hours: 9-11 hrs
Related website: https://herrlab.berkeley.edu
Biological & Health Sciences Engineering, Design & Technologies