Full-stack software engineering volunteer for AI-based big medical imaging data analysis pipeline development
We have several volunteer positions available for individuals interested in full stack software development to support our lab’s research and its real-world translation in the fields of medical image analysis, artificial intelligence (AI) and machine (deep) learning.
The overarching mission of our lab is to improve the delivery and effectiveness of healthcare systems through the integration of automated software pipelines powered by the state-of-the-art AI and big-data technologies. Our present goal is to enable clinics with cutting-edge automated medical image analysis software tools accessible via user-friendly graphical user interfaces (GUIs) to provide visual and informationally-rich measurements from images that clinicians could use to make better decisions regarding diagnosis, prognosis, treatment and follow-up care.
The expertise we need right now is in core software development and these projects involve working on one or more aspects of the medical image analysis software production process. Broadly, the software development projects fall under the following four areas:
- Web design & development: Work on the further development of our CERAMICCA (Cloud Engine Resource for Accelerated Medical Image Computing for Clinical Applications) web portal https://ceramicca.ensc.sfu.ca to improve its functionality, implement new features and enhance the user experience (UX).
- Database systems: Contribute to the design, deployment and maintenance of a robust database management system using software frameworks such as XNAT, LORIS etc. to efficiently handle and provide reliable access to our ever increasing data footprint of raw medical images and corresponding processed outputs, currently close to half a petabyte (PB).
- Big data processing infrastructure: Join the continuous development of our Meta-Scheduler software suite which federates the computing power of heterogeneous high performance computing (HPC), cloud computing and graphics processing unit (GPU) computing resources and makes it available through a unified platform, along with providing project management capabilities to facilitate rapid fault-tolerant big data high-throughput processing.
- Medical image manual labeling tools: Create GUIs with customized medical image manual annotation/segmentation, visualization and quality control (QC) tools to aid in the generation of high quality labeled training and validation datasets for the development of machine (deep) learning based algorithms for medical image analysis. Create GUIs to present multimodal and rich information for presentation of computational measures overlaid on structural and functional images.
Requirements and Availability
This position is ideally suited for Computer science/Math/Engineering/Statistics/Data Science graduate and undergraduate students interested in honing their programming skills through working on challenging software engineering projects with real-world applications. However, anyone with the relevant programming background, interested in contributing to our projects is welcome to apply. The training, mentorship, and the opportunity to actively participate in and contribute to cutting-edge research are available equitably, and our group has been especially welcoming and successful in attracting and retaining students and researchers of diverse identities and backgrounds.
We do not have a fixed schedule for the volunteer position. Volunteers are able to work remotely and are expected to manage their time flexibly while meeting deliverable deadlines. Volunteers are expected to dedicate a minimum of 5-10 hours per week.
How will this poisition benefit you?
Apply via email with subject "[faisal-lab] [recruitment] Software engineering volunteer - AI-based big medical imaging data analysis pipeline development" indicating your interest. Include a few details about yourself and please attach your resume.
Contact: "Dr. Mirza Faisal Beg" at firstname.lastname@example.org.
Location: ASB 10873 at Simon Fraser University (8888 University Drive, Burnaby, British Columbia, Canada) - volunteers able to work remotely.