*** Please note: The deadline for this call has now passed. Thank you to all the applicants and for your interest. The below information is being left up for reference.***
This program will help researchers refine existing software tools to improve usability and robustness or build new tools, disseminate research software beyond the research space in which it is created, and enhance existing functionality.
The Research Software Development Support Program provides research groups access to a professional research software developer. The research software developer will work alongside the research group on a part-time (up to a 0.5 FTE) basis for 2 to 6 months.
Interested researchers can apply to this program by completing this short application form (Please note: This form was created for use with Adobe Acrobat. Opening the form with other software, like Mac's Preview, may result in it not responding correctly.) that:
Please email the application form as a PDF document to firstname.lastname@example.org by October 21, 2022, at 12 pm noon EST. The file should be named [Last name, First name DSI ResSoftware].
Researchers are invited to meet with the DSI’s Research Software Developer to discuss their projects before submitting their applications. This will likely be more important for researchers less familiar with software development and less important for those with good software development experience and ongoing software projects. Please reach out to the developer directly at email@example.com to schedule a meeting. To make this meeting as productive as possible, applicants are encouraged to complete the research software development checklist ahead of time. This checklist also contains information that may be useful to include in the application.
Applications will be assessed by a member of the DSI Executive, the software developer team, and additional UofT staff with software development expertise using the criteria outlined below.
Highly ranked applications may be invited to discuss their proposals in more detail with the selection committee who will then pick the three or six projects that they consider to be the best fit for the program. During the assessment process, information about the application may be posted publicly at https://github.com/UTorontoDataScience/research-software-development-support/issues to facilitate project tracking and selection in a transparent manner.
Professor Gary Bader, Associate Director, Data Management, Research Software, Advanced Research Computing, Data Sciences Institute, hosted an information session on research software development support on November 11, 2021. The webinar’s recording and slides are available here as are the PDF Slides.
For more information, please contact: firstname.lastname@example.org
With the help of the DSI’s software development support program, Dr. Gregory Schwartz and his team at the University Health Network, are working on a suite of tools designed for clustering and visualizing single-cell data, to better understand heterogeneity and drug resistance in cancer.
Alan Moses from the Department of Cell & Systems Biology, Faculty of Arts & Science, and Julie Forman-Kay from The Hospital of Sick Children are working to create a software program to help the research community with intrinsically disordered regions.
Dorothea Kullmann from the Department of French, Faculty of Arts & Science will work with the DSI to develop a database consisting partly of late medieval manuscripts.
Eunice Eunhee Jang from the Department of Applied Psychology and Human Development, OISE is working on curriculum-based learning tools that assess and track children’s emergent literacy and language development.
Ewan Dunbar from the Department of French, Faculty of Arts & Science is working to create a web interface that allows speech researchers to upload audio files and download “speech features” useful for speech processing.
Gregory Schwartz, University Health Network, and his team identified rare cancer cells which may contribute to disease progression. He is working to better understand cellular heterogeneity, by developing a suite of tools for clustering and visualizing single-cell data called TooManyCells.
Laura C. Rosella, Dalla Lana School of Public Health and Birsen Donmez, Department of Mechanical and Industrial Engineering, Faculty of Applied Science and Engineering are working to apply Human Factors Engineering methods to build a user-friendly decision support tool for the Chronic Disease Population Risk Tool (CDPoRT).