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Postgraduate study

Bioinformatics (with Advanced Practice) MSc

As biological sciences have become more data driven, bioinformatics is now central to modern biological research, from genetics, nutrition and epidemiology to ecology, neuroscience and biomedicine.


Course overview

This programme teaches you how to manage and manipulate large datasets to reveal new insights in biological sciences. You get intensive training in a computer-based approach to biological research. You develop the computational and analytical understanding necessary as a platform for processing biological data. This involves the appreciation of biochemistry and molecular biology, together with IT and specialist skills in computer programming, data analysis, statistics and computational biology for multidisciplinary careers in research.

Where possible this course is taught at ATMOS building at the University’s Darlington campus. There are three routes you can select from to gain a postgraduate master’s award:

  • MSc Bioinformatics – one year full time
  • MSc Bioinformatics – two years part time
  • MSc Bioinformatics (with Advanced Practice) – two years full time

The one-year programme is a great option if you want to gain a traditional MSc qualification. The two-year master’s degree with advanced practice enhances your qualification by adding a vocational or research based internship to the one-year master’s programme. A vocational internship is a great way to gain work experience and give your CV a competitive edge. A research internship provides you with the opportunity to develop your analytical, team-working, research and academic skills by working alongside a research team in an academic setting. We guarantee a research internship, but cannot guarantee a vocational internship. We will, however, provide you with practical support and advice on how to find and secure your own vocational internship position should you prefer this type of internship.

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Course details

For the MSc with advanced practice, you complete 120 credits of taught modules, a 60-credit master’s research project and 60 credits of advanced practice.

Course structure

Core modules

Advanced/Applied Practice in Health & Life Sciences

You complete advanced practice (AP) when you study our two-year postgraduate courses. Completed over one semester (12 weeks), you gain additional experience and enhance your employability and academic learning.
You normally complete one of the below AP internship types:
• a research or development internship developed by Teesside University staff
• an employer-led internship developed by the employer partner
• a virtual internship working on projects for an external organisation
• a vocational internship with an external organisation.
All internships are located at our Middlesbrough or Darlington campus (including NHC), apart from the vocational internship which is located at the external organisation.
The AP internship is related to your course. You receive preparatory sessions, normally in the semester before (delivered by our Student Futures team) and an introductory session from the module leader.

You are expected to complete at least 400 hours of AP work, including preparation for AP, induction, training and any personal or professional development completed.

You receive 12 hours of supervision (normally 1 hour per week) and are assigned an AP supervisor (a member of University staff) to support and assess your work. Your supervisor’s role varies depending upon the internship type (explained in the learning strategy). As a minimum, they meet with you at the start, mid-point and end of the internship, coordinate meetings and are the point of contact for internship providers. You are also allocated a work-based mentor who functions as your supervisor when completing specific internship types.

Bioinformatics Analysis Techniques and Tools

Develop advanced bioinformatics knowledge and practical data analysis skills. You are introduced to the core knowledge and computational practices used in the bioinformatics field. Study the application of state-of-the-art bioinformatics and computational biology approaches to problem solving relating to high-throughput microarray, next generation sequencing and functional genomics datasets derived from real or simulated research scenarios. IT laboratories are paired with lectures, allowing you to practice and further develop your core computing and problem-solving skills.

Data Analytics

Gain core knowledge in statistical methods and the practical skills to apply and perform data analytics. This is essential to data scientists in the bioinformatics field. Develop a solid foundation in statistical concepts and the different data analysis approaches and pipelines used in bioinformatics studies. Commercial software packages, such as SPSS are introduced for data analysis and visualisation. IT laboratories are coupled to the lectures and enable you to test out your new skills, tackle exercises, and work on project code to manipulate, process and interpret biological data.

Genomic Technologies

Explore ‘omics’ technologies and bioinformatics and learn about most recent technologies, next generation sequencing (such as Nanostring and Illumina platforms), CRISPR-Cas system and genome editing, genomic and bioinformatics analyses, genomic application for disease treatment and prevention (pharmacogenomics), personalised medicine as well as ethical challenges in this field.

Life Science Research Project

You undertake a major independent practical research project in your discipline while fully integrated within a research team. Reflecting staff expertise, you pursue many discipline-related topics, including medical, industrial and environmental microbiology, molecular, cell and system biology, recombinant DNA technology, protein biochemistry, structural biology, fermentation, bioengineering and many other areas, using the state-of-the-art analytical and digital infrastructure at the National Horizons Centre. You complete a hypothesis-driven project using appropriate discipline-specific laboratory, database or computational research methodologies to interrogate a hypothesis in a specialised area of the life sciences. You are expected to work at a level recognised to be at the forefront of the discipline. Key skills in research and knowledge creation are developed. You must demonstrate the capacity for comprehensive and objective analysis, and for developing innovative and constructive proposals for the solution to the project topic. Supervisors provide guidance to support you, but a high degree of autonomy is required. You are supported by working within a research team, and by technical and learning support staff.

Proteomic Technologies

You explore ‘omics’ technologies focused on the translational and post-translational mechanisms. You learn about most recent technologies, next generation sequencing, proteomics, phospho-proteomics, metabolomics (such as mass spectrometry) bioinformatics analyses, applications for disease treatment and prevention (pharmacogenomics), personalised medicine and ethical challenges in this field. One of two modules dedicated to the exploring ‘omics’ technologies. Taught through a combination of interactive lecture and seminars.

Python for Bioinformatics

You are introduced to the popular programming language of Python, a powerful scripting language in bioscience and found throughout bioinformatics and scientific computing. The first half of the module introduces basic principles of coding and interface interaction. In the second half you learn a script language for statistical computing and graphics and more advanced practices. Integrated development environments (Spyder and Jupyter) are learnt for writing, running, and debugging codes for Python. To turn analyses into high quality documents, reports, and presentations, JupyterLab will be applied as a popular library. IT Laboratories are coupled to the lectures where you test out your new skills, tackle exercises, and work on project code to manipulate, process and interpret biological data.

R for Bioinformatics

You are introduced to the popular programming language of R, which is widely used and powerful in bioscience, bioinformatics and scientific computing. R especially shines where a variety of statistical tools are required (such as RNA-Seq and population genomics) and in the generation of publication-quality graphs and figures. In the first half of the module, basic principles of coding and interface interaction are introduced. In the second half you learn a script language for statistical computing and graphics and more advanced practices. Integrated development environments (such as RStudio) are introduced for writing, running and debugging codes for R. To turn analyses into high quality documents, reports and presentations, R Markdown will be applied as a popular library. IT Laboratories are coupled to the lectures where you test out your new skills, tackle exercises, and work on project code to manipulate, process and interpret biological data.


Optional modules

Modules offered may vary.


How you learn

Making the transition to postgraduate-level study can be challenging. Support with making this transition is seen as an important element of this programme.

The Data Analytics and Algorithms for Bioinformatics and Database Theory and Application modules help you understand the requirements of academic study at postgraduate level, to enhance your skills in academic writing and referencing, and to help you develop the skills necessary to operate professionally and ethically in planning and implementing a master’s-level research project.

By including work-based problem-solving projects and case study exercises this programme emphasises real-world working. This helps to develop your critical thinking skills as well as your ability to design, execute and present findings of research, allowing you to cultivate the skills employers are seeking to set you on a successful career path.

A significant feature of the programme is the opportunity to gain experience of working in state-of-the-art bioinformatics research facilities within the National Horizon Centre

How you are assessed

Modules are assessed by a variety of methods including exams and in-course assessment with some using other approaches such as group work, verbal or poster presentations. 

Your Advanced Practice module is assessed by an individual written reflective report (3,000 words) together with a study or workplace log, where appropriate, and through a poster presentation.


Entry requirements

Applicants are normally expected to have at least a UK 2.2 honours degree, or equivalent, in a subject related to life or physical sciences. If your first degree is not in one of the subject areas listed above please contact our admissions team for guidance and advice on how you might become eligible. We may be able to offer you alternative access routes.

International applicants can find out what qualifications they need by visiting Your Country

In addition, international students normally need at least a 6.0, with no component below 5.5, in the International Language Testing System (IELTS) test.

For general information please see our overview of entry requirements

International applicants can find out what qualifications they need by visiting Your Country



Work placement

There may be short-term placement opportunities, particularly during the project phase of the course.

Career opportunities

Our bioinformatics programme equips you with a strong foundation for further PhD research or for prospective employment. There is an increasing demand for bioinformatics skills across the biotechnology, life sciences and pharmaceutical sectors. The ability to manage, analyse, integrate and visualise big data using technologies such as Python and R is also applicable to fields including software development, data analytics and finance.


Information for international applicants


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2024/25 entry

Fee for UK applicants
£4,770 a year

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Fee for international applicants
£10,000 a year

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  • Length: September enrolment: 20 months, including a summer break; January enrolment: 2 years, including two summer breaks
  • Start date: September or January
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