Computational neuroscience is an interdisciplinary science in which biological principles inspire the development of mathematical models and computer algorithms, numerical simulations are used to test models of neural circuit function, and mathematical models, theoretical analysis and abstractions of the brain are used to improve our understanding of the principles that govern brain development, structure, physiology and cognition.
The UCalgary Graduate Interdisciplinary Specialization in Computational Neuroscience includes coursework covering the fundamentals of neuroscience, advanced statistics, mathematical modeling, network sciences, computational physics, machine learning and other related areas.
The program will aim to recruit a diverse population of students and provide an inclusive and supportive environment in which all learners can succeed.
The goal of the specialization is to train students in both fundamentals of neuroscience and computational modeling / data sciences so that graduates are:
- Well-equipped to undertake technical projects that use computational principles to study nervous system function or develop biologically inspired systems.
- Skilled in areas that will make them highly employable in the biotechnology field.
Find more information about the program requirements, potential supervisors and how to apply.