Computational Physics
This Computational Physics program at University of Winnipeg leads to a Bachelor of Science degree (4-year Honours), which provides excellent preparation for entry into graduate programs in computer science or physics, and direct entry into industry where analytical and computing skills gained in the program are in demand.
Quick Facts
|
|
| Full-time: |
4 years |
| Starting in: |
September |
| Tuition Fee: |
15,810 CAD per year |
| Location: |
Winnipeg Campus, Winnipeg, Canada |
From the transistor to the internet to the quantum computer, physicists have always played a leading role in the development of new computing hardware and methods.
Computational Physics at University of Winnipeg is the study of physics using computational methods. It is an expanding field that combines computer science, physics, and applied mathematics to solve complex problems.
In the computational physics stream, you will learn all about the fundamental laws of nature, while developing real world skills in numerical methods and coding, as well as data handling and visualization.
You will also learn about leading edge techniques such as quantum computing and machine learning. Professors in the physics department conduct research in subatomic physics, medical physics, theoretical physics, and applications to developing fields of technology like digital agriculture.
All of these research areas make use of computing to solve problems, and many students participate in research using computational resources under the direction of faculty.
As with the main physics program, students may find summer employment with the various research groups.
If you are interested in becoming a teacher, both physics and computer science are teachable subjects in education.
Career Possibilities
The analytical and computing skills developed in obtaining a Computational Physics degree can be applied to almost any field imaginable, including engineering, finance, climate modelling, agriculture, space science, astronomy, computer gaming and animation. Data scientists, for example, are in high demand in all of the social, life, and natural sciences, as well as the government, health, and insurance sectors.
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