Research Summer Student 2026

  • Contract
  • Department: Research
  • Compensation: CAD 18.67 - CAD 22.24 - hourly

Company Description

UHN is Canada’s #1 hospital and the world’s #1 publicly funded hospital. With 10 sites and more than 44,000 TeamUHN members, UHN consists of Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute, The Michener Institute of Education and West Park Healthcare Centre. As Canada's top research hospital, the scope of biomedical research and complexity of cases at UHN have made it a national and international source for discovery, education and patient care. UHN has the largest hospital-based research program in Canada, with major research in neurosciences, cardiology, transplantation, oncology, surgical innovation, infectious diseases, genomic medicine and rehabilitation medicine. UHN is a research hospital affiliated with the University of Toronto.

UHN’s vision is to build A Healthier World and it’s only because of the talented and dedicated people who work here that we are continually bringing that vision closer to reality.

www.uhn.ca

Job Description

Union: Non-Union
Number of Vacancies: 1
New or Replacement Position: New
Site: Hydro Place - 700 University Avenue
Department: Research
Reports to: Clinician Investigator, Radiation Medicine Program
Salary Range: $18.67- $22.24 Per Hour
Hours: 37.5 Hours Per Week
Shifts: Monday -  Friday
Status: Temporary Full-time
Closing Date: May 27, 2026

Position Summary:
The Radiation Medicine Program (RMP) at the Princess Margaret Cancer Centre is a global leader in radiation oncology, integrating clinical care, research, and education to improve cancer treatment outcomes. Through interdisciplinary collaboration, RMP advances innovative technologies in radiation therapy, dosimetry, and patient safety.

This summer student project focuses on exploring the potential of quantum computing to accelerate Monte Carlo dose calculations in radiotherapy. Monte Carlo simulation is considered the gold standard for radiation dose calculation due to its high accuracy in modeling radiation transport. However, its clinical and research application is often limited by significant computational demands.

The student will contribute to an exploratory research project that examines how quantum computing concepts, implemented using Python-based quantum simulators and hybrid quantum and classical approaches, can improve the computational efficiency of dose calculations. Working within a multidisciplinary team across the University Health Network and the University of Toronto, the student will gain hands-on experience in medical physics, computational modeling, and emerging quantum technologies.

Duties:

  • Develop and implement a simplified Monte Carlo dose calculation model in Python as a classical reference framework.
  • Design and test basic quantum computing circuits using Python-based quantum computing simulators (e.g., Qiskit or similar tools).
  • Compare classical and quantum-based approaches in terms of accuracy, uncertainty, and computational performance.
  • Explore hybrid quantum–classical methods for improving efficiency in radiation dose estimation.
  • Perform data analysis and interpret simulation results related to dose calculation and computational performance.
  • Conduct literature reviews on Monte Carlo methods, radiotherapy physics, and quantum computing applications.
  • Prepare reports, documentation, and presentations summarizing research findings and project outcomes.

Qualifications

  • Must be 16 years of age or older, per UHN policy
  • Must be enrolled in a Bachelors or Postgraduate program, Physics, Medical Physics, Engineering, Computer Science, or a related field.
  • Your appointment runs between May 2026 - August 31, 2026
  • Strong interest in computational physics, radiotherapy, or quantum computing.
  • Experience with programming in Python (required); familiarity with scientific computing libraries is an asset.
  • Basic understanding of radiation physics, Monte Carlo methods, or numerical simulation is an asset.
  • Strong analytical and problem-solving skills with attention to detail.
  • Excellent written and verbal communication skills.
  • Ability to work independently and collaboratively in a multidisciplinary research environment.

Additional Information

Why join UHN?

In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor, allowing you to find value where it matters most to you, now and throughout your career at UHN.

  • Competitive offer packages
  • Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp.com/)
  • Close access to Transit and UHN shuttle service
  • A flexible work environment
  • Opportunities for development and promotions within a large organization
  • Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.)

Current UHN employees must have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN's attendance management program, to be eligible for consideration.

All applications must be submitted before the posting close date.

UHN uses email to communicate with selected candidates.  Please ensure you check your email regularly.

Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading, inaccurate or incorrect, UHN reserves the right to discontinue with the consideration of their application.

UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.

We thank all applicants for their interest, however, only those selected for further consideration will be contacted.

Privacy Notice