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Master of Computational Biology (MC-COMPBIO) // Attributes, outcomes and skills
You’re currently viewing the 2021 version of this course
About this course
Coordinator
Jennifer Flegg
Intended learning outcomes
On completion of this course the student is expected to achieve:
- A broad education in computational biology with strong foundations in computer science, statistics and biological modelling;
- Significant expertise in a specific area of computational biology;
- The opportunity to integrate and apply this learning to produce solutions for practical biological problems;
- The ability to adapt to a rapidly evolving field;
Generic skills
- The ability to interact in a cross-cultural environment
- The ability to develop time and project management skills
- The ability to exercise critical judgement and operate in both a team environment and/or with a high level of personal autonomy and accountability
- The ability to exercise independent thinking and high-level problem solving skills
Graduate attributes
Graduates will:
- have the ability to demonstrate advanced independent critical enquiry, analysis and reflection in the field of computational biology;
- have a strong sense of intellectual integrity and the ethics of scholarship;
- have in-depth knowledge of the key tools and methods used in computational biology;
- reach a high level of achievement in writing, project or research activities, computationally-based problem-solving and communication;
- be critical and creative thinkers, particularly in relation to manipulation and analysis of large biological data sets, with an aptitude for continued self-directed learning;
- be able to examine critically, synthesise and evaluate knowledge across a range of biological disciplines using a range of advanced computational, statistical and mathematical techniques;
- have a set of flexible and transferable skills for different types of employment;
- be able to initiate and implement constructive change in their communities, including professions and workplaces
Last updated: 19 April 2024