MSc in Applied Bioinformatics and Genetic Epidemiology, Cardiff University

Cardiff,

12 Months

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About this course

This MSc programme is designed to equip students with the skills to explore, analyze, and interpret biological data, with a focus on genetic epidemiology. It combines instruction in bioinformatics and genetic epidemiology to prepare graduates for careers in research, biotechnology, and the pharmaceutical and healthcare industries. The course emphasizes gene discovery methods like GWAS and explores variations such as CNV, alongside post-GWAS approaches like pathway analysis and polygenic epidemiological methods. It aims to develop computational and statistical bioscience skills, alongside practical research experience through case studies and a research dissertation, all within a year of full-time study. The curriculum continuously evolves with advances in genomic technologies, ensuring students receive contemporary training. Delivery includes lectures, practicals, group work, and a significant research project, making it a comprehensive pathway for those interested in applying bioinformatics to health and disease.

Why this course is highly recommended

This programme was created in response to the increasing need for skilled bioinformaticians in research and industry, especially as genomic technologies continue to advance. It offers contemporary training in essential skills like bioinformatics software, statistical methods, and research techniques. With hands-on experience in real-world data analysis through case studies and a research project, students gain practical skills highly valued in academia, biotech, and healthcare. The programme’s focus on multidisciplinary skills and core knowledge makes graduates competitive for roles in research, biotech, pharmaceuticals, and health industries, or for pursuing further studies like a PhD.

Specialisation

The course focuses specifically on genetic epidemiology within the broader field of bioinformatics. It offers deep instruction in computational and statistical approaches tailored for analyzing genetic data, including gene discovery techniques like GWAS, CNV analysis, and post-GWAS methods such as pathway and network analysis. The programme is suitable for students from life sciences, mathematics, or computing backgrounds seeking to specialize in understanding genetic factors influencing health and disease, and their environmental interactions.

Course fees

Application fees

1st year tuition fees

29.77L

Living cost

Degree requirements

Applicants need a 2:1 honours degree or equivalent in a relevant subject, such as life sciences, mathematics, or computing. Those with a 2:2 may be considered individually. In addition, an IELTS score of 6.5 overall with 6.5 in all subskills or an accepted equivalent is required. If the degree or test results are pending, provisional evidence should be provided. For applicants without a degree or with a 2:2, relevant professional experience may be considered. A personal statement outlining motivation, skills, and experience is also necessary.

English language test

TOEFL

IELTS

6.5

DUOLINGO

PTE

Career prospects

Graduates from this programme are prepared for careers in academic research, biotech, pharmaceuticals, and healthcare industries, particularly roles requiring bioinformatics and genetic data analysis. The course’s focus on computational and statistical biosciences equips students to work effectively in multidisciplinary environments. Past graduates have entered PhD programs or secured research and data science roles, with many working in bioinformatics or related fields within biomedical and health sectors.

FAQs

What is the duration of the course?

The MSc is a full-time programme lasting one year, spanning from late September to September of the following year.

What are the entry requirements?

Applicants need a relevant degree with a minimum of a 2:1 honours classification and an IELTS score of 6.5 overall with 6.5 in all subskills, or equivalent evidence.