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Bioinformatics and Genetic Epidemiology

Cardiff University
1-3 years
Full time/part time
Master's degree
Scholarships available
On campus
26 September 2022

About this program

Bioinformatics and Genetic Epidemiology

The aim of this programme is to provide individuals with a platform to explore, analyse and interpret contemporary biological data. This course offers Masters level instruction in Bioinformatics and Genetic Epidemiology with a focus in genetic epidemiology.

With a focus on genetic epidemiology, this programme is ideal for graduates from a life sciences, mathematics, or computer sciences discipline.

It will provide you with the skills and knowledge of computational and statistical biosciences to prepare you for a challenging career in academic research, biotechnology, or the pharmaceutical and healthcare industries.

Bioinformatics is the field of study that utilises computational tools to understand biology. Genetic Epidemiology is the study of how genetic factors play a role in determining health and disease, and their interplay with the environment. As well as developing core skills in computational and statistical biosciences, you will focus gene discovery approaches including GWAS, explore copy-number variation (CNV) analysis, and post-GWAS approached such as pathway/network, gene-set and polygenic epidemiological methods.

Admission requirements

Admissions criteria

In addition to satisfying the requirements of the Cardiff University General Entrance Requirements, meeting English language requirements IELTS of at least 7.5 with 6.5 in each subsection, at the discretion of the relevant Board of Studies, applicants will:

  • normally possess a minimum of an upper second-class (or equivalent) primary degree in a bioscience or computing or mathematics/statistics.
  • Graduates in other subject areas with a degree awarded by a recognised Institution will be considered by the course Admissions Committee.At the discretion of the Board of Studies, non-graduates whose relative lack of formal qualifications or graduates who were awarded a lower-second class (or equivalent) degree may be accepted for study by compensation for their relevant work experience. The candidate must provide evidence that they have held, for a minimum period of two years, a position of responsibility relevant to the programme.

English Language Requirements:

Applicants who require a Student visa to study in the UK must present an acceptable English language qualification in order to meet UKVI (UK Visas and Immigration) requirements.

For more information about tuition fee, please visit the university website.

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Program content

The modules shown are an example of the typical curriculum and will be reviewed prior to the 2022/23 academic year. The final modules will be published by September 2022.

Year one

  • Computing for Bioinformatics and Genetic Epidemiology
  • Statistics for Bioinformatics and Genetic Epidemiology
  • Genetic Epidemiology: Association and Linkage

Year two

  • Introduction to Bioinformatics
  • Case Studies in Bioinformatics and Biostatistics
  • Post-GWAS Genetic Epidemiology

Year three

  • Dissertation: Genetic Epidemiology

Scholarships & funding

For more information about scholarships, please visit the university website.


Full-Time tuition fees

  • UK students: £10,200
  • International students: £23,450

Part-Time tuition fees

  • UK students: £5,100
  • International students: £11,725


What skills will I practise and develop?

Upon completing the Programme, you will be able to demonstrate:

  • a systematic understanding of the principles of statistics, biosciences and computer science that are the foundations of genetic epidemiology and bioinformatics
  • a knowledge of current bioinformatics software and databases and their applicability to solving bioinformatics problems in the field and in their own research
  • a keen awareness, understanding and critical appreciation of the wide variety of statistical methods available to analyse genetic data together with appreciation of the issues involved in study design
  • a knowledge of statistical software used to analyse omics data and the situations in which the packages should/should not be applied.
  • integrate acquired knowledge and understanding with practical skills resulting in a sound approach to problem solving;
  • synthesise information from a variety of sources at the forefront of Genomics and Bioinformatics;
  • critically evaluate different approaches to solving problems and to demonstrate their applicability, strengths and weaknesses;
  • formulate hypotheses and use analytical skills to test these hypotheses. Interpret the results and make decisions in the light of all available information in possibly complex and unpredictable situations;
  • undertake a semi-independent piece of original research or critical review demonstrating self-initiative, responsibility for planning and carrying out tasks, tackling and solving research problems
  • the ability to assess the correct type of analysis for a dataset and to perform it using an appropriate computer package
  • competency in accessing and using bioinformatics tools from a variety of sources
  • computer programming skills and competency in good program design
  • the ability to design, implement and analyse algorithms for bioinformatics applications
  • the ability to produce case study reports on major topics within the fields of bioinformatics and biostatistics
  • competent research skills such as literature searches
  • work independently, to manage his/her own time and to take responsibility for learning required for continued professional development
  • effectively manage individual tasks and larger scale projects identifying and resolving possible obstacles
  • work as part of interdisciplinary teams, identifying individual;s strengths and weaknesses and allocating work accordingly to meet the team;s objectives
  • competently use information technology such as e-mail, word-processors, software tools and the world-wide web
  • transfer computing skills and concepts to subsequently unfamiliar packages/languages/databases
  • present information, understanding and arguments using effective communication (written and oral) with awareness of intended audience

Career paths

Career prospects

We are committed to developing transferable skills and to improving graduate employability. We want highly capable graduate informaticians who can fulfil the growing bioinformatics needs of local, national and international employers. That is why this programme has been designed with the needs of academic research, the biotechnology, pharmaceutical and health care industries in mind. Instruction in computational and statistical biosciences will enable you to work effectively within a multidisciplinary bioinformatics arena.

Our first cohort of five students enrolled to the reconfigured MSc in September 2018. As of July 2019 one student has accepted a PhD post, and two have accepted research associate posts in bioinformatics. We eagerly await the result of upcoming interviews!

Historically, from 2004-2017 this programme has seen approximately 24% students enter a PhD directly related to bioinformatics, 17% students entered other PhD in other areas of biomedicine; 10% entered MSc/PGCE/medical degrees; and approximately 49% gained employment related to bioinformatics, biostatistics or other data science .

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About this institute

Cardiff University

Founded in 1883, Cardiff University combines a prestigious heritage with impressive modern facilities, on one of the most beautiful campuses in the UK. As part of the Russell Group, our students benefit from our outstanding research quality and reputation, while...

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Contact info

Cardiff University

CF10 3AT Cardiff

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