You are now in the main content area

Undergraduate Student Research Awards

The NSERC Undergraduate Student Research Awards (USRA) program provides eligible students the opportunity to take on a one-term university research position under the supervision of a faculty member. The Department of Physics encourages eligible students to apply. Recipients gain valuable work experience in the research environment, contribute directly to active projects, and explore their potential for graduate studies.

Below are some open positions currently available. Students may also contact faculty not listed to see if project opportunities not listed exist. Candidates are selected through a competitive process. To apply, contact the supervising professor listed for the project that interests you.

2021 NSERC USRA Information Session

Date: Friday, February 5th, 2021
Time: 12:00pm (noon) - 1:00pm
Location: Virtual Zoom Call, external link

Kindly RSVP  

Important Dates

Ryerson Information session: Friday, February 5 12:00pm (EST)
Application Submission deadline: Thursday, February 25 by 4:00pm (EST)
Departmental reviews/rankings due to OVPRI: Friday, March 12 by 4:00pm (EST)
Notification of Decision to applicants/supervisors: Late March/Early April

Please visit OVPRI for more details about the application process and the deadlines.

Modeling protein concentration fluctuations in mitochondrial networks

Description:
Mitochondria form tubular networks that are dynamic, with fusion and fission events that restructure the network and import of newly-synthesized proteins. The concentration of proteins within mitochondria can vary greatly between individual mitochondria in a cell. The student completing this project will develop stochastic simulations to quantitatively explore how the dynamic mitochondrial processes control protein concentration variation. This project is motivated by experimental data showing that mutations affecting mitochondrial dynamics substantially change the pattern of protein concentration variation. This project will develop skills for building simulations and computationally implementing stochasticity and physical models of cell biology.

Supervisor:
Aidan Brown
Email

Monte carlo simulation of amorphous solids

Description:
Apply a large enough force to any amorphous solid and it will break. This yielding transition is known to be surprisingly universal, whether considered for an emulsion, metallic glass, or granular material. However, many details of the yielding transition remain mysterious. In this project, you will simulate a simplified model of yielding in amorphous matter, using the Monte Carlo technique, and compare the outcomes with results from molecular dynamics simulations and experiments. The programming can be done either in MATLAB or Python and can lead to a scientific publication for a motivated student.

Supervisor:
Eric De Giuli
Email

Computational virophysics

Description:
In physics, our understanding of phenomena is expressed in terms of math expressions, e.g. F=ma or E=mc^2, which also allows us to make verifiable predictions beyond experimental observations. In virology, there is little or no math, and this makes robust validation of knowledge and prediction impossible: let's work together to fix this! In your project, you will use scientific programming (probably coding in python) and math (mostly ODEs) to describe and study a specific aspect of a virus infection in vitro, like flu or VSV. The specifics of the project will depend on your skills and interests. You can read about work in my group at Virophysics Group website. Contact me(cbeau@ryerson.ca) to find out more.

Supervisor:
Catherine Beauchemin
Email

Using quantitative ultrasound methods for assessing kidney fibrosis

Description:
Chronic Kidney Disease (CKD) affects approximately 10% of the population and it is globally increasing due to the rise of comorbidities, such as diabetes and hypertension. There is no cure for CKD, but kidney replacement via transplantation can offer a long-term remedy. However, not all donated kidneys are of the same quality, with many of them contain a significant amount of scarring or fibrosis. Fibrosis of the kidneys impairs organ function and can lead to failure of the transplant. Physicians currently don’t have a method available of assessing the quality of kidney transplants. Ultrasound imaging is an accesible, non-invasive, and widely available modality that can potentially assess kidney fibrosis.

This project will involve the development of ultrasound tissue characterization approaches based on signal processing of the radiofrequency data from the backscatter echoes. Specifically, the student will gain proficiency in a number of analysis signal processing methods that involve both time (envelope statistics, speckle decorrelation, M-mode) and frequency (spectrum, cepstrum) domain analysis. In collaborations with nephrologists at St. Michael’s Hospital, the clinical goal of this project is to develop quantitative methods for monitoring kidney damage using ultrasound imaging. All the data required to complete this project has been collected in mouse, pig and human kidneys and the project can be completed remotely.

Supervisor:
Michael Kolios
Email

Learn more about Student Research at Ryerson.