MSc Big Data Biology
Cardiff, United Kingdom
DURATION
1 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
Request application deadline
EARLIEST START DATE
Sep 2025
TUITION FEES
GBP 27,450 / per year *
STUDY FORMAT
On-Campus
* for overseas | for home: £11,450
Introduction
From microbiomes, phenomes and genomes to whole ecosystems, modern biology generates a vast amount of data. The scale and nature of this information requires a new generation of scientists with the skills to harvest, analyse, manipulate and interpret big data, and to link this analysis to underlying mechanisms through mathematical and computational modelling.
As a student in our innovative MSc Big Data Biology, you will have the opportunity to explore the cutting-edge platforms used in modern biological analysis. You will learn about the statistical and computational approaches required to analyse the big data generated and mine the growing repositories of ‘omics data that now exist within biology.
A core distinguishing feature of our program is that it will enable you to interface your big data analysis to dynamical systems and network theory, rather than relying solely on performing pattern analysis and/or AI methods to data. This unique big data modelling approach will allow you to test hypotheses and analyse models to uncover biological mechanisms from high-throughput data sets. You will explore how big data can be better interpreted and mined using biological understanding and conversely, how it can generate novel biological insights.
The course is designed to equip you with the skills to work on “real-life” data problems. You will become proficient at using core tools and approaches for big data analysis and build confidence in critically selecting and applying these approaches to address a wide scope of biological questions. After completing the first core modules, you will apply the skills gained to solve a big data scenario for a “client” – a real-life problem faced by a research group within a university, industry or government organisation.
The structure of the course provides a broad overview of systems biology, as well as enabling you to specialise in an area of your interest through an extensive range of research opportunities. You will complete the programme with a solid grounding in both systems biology and bioinformatics. Furthermore, you will be able to improve your transferable skills, such as working in interdisciplinary teams, learning how to master new software in a structured manner, writing reports or grants writing, and delivering science presentations – all important skills for an early career researcher.
Big Data Biology is a progressive and exciting area of science. Advancing our understanding of living systems depends on unlocking the potential of big data, from molecules to the biosphere. This programme has been specifically designed to ensure that you are fully prepared for a career in industry or academic research and that your skills closely reflect those currently sought by employers. Crucially, you will also learn how to keep pace with future developments in the field of big data biology by learning how to effectively absorb and employ new strategies and technology.
Why Study this Course
Our innovative MSc will enable you to use cutting-edge, big-data platforms to tackle issues from developmental biology to disease surveillance and ecology.
A Unique, Holistic Approach
Learn how to combine big data with modelling to derive a mechanistic understanding of biological processes.
Real-life Application
Apply your skills and knowledge to real-life scenarios, specifically designed to align with problem-solving in the workplace.
Inter-disciplinary collaboration
Join an exciting and growing network of students and academics working in predictive biology.
Ranked 4th in the UK and 27th in the World
Our School is ranked highly for Biological Sciences by the 2021 Shanghai Ranking Global Ranking of Academic Subjects.
Admissions
Scholarships and Funding
We are committed to investing up to a total of £500,000 in this high-value competitive scholarship scheme to support UK students who are planning to start an eligible Master’s programme in 2024/25.
The Scholarships are each worth £3,000 and will be awarded in the form of a tuition fee discount.
Eligibility
UK students are eligible to apply for the Scholarship. You normally need to have achieved at least a 2.1 or equivalent in your first degree to be eligible. You need to submit an application to study at Cardiff University and be made an offer to study before your fee status can be confirmed.
Curriculum
The course runs for 12 months full-time. Students undertake modules to the value of 180 credits.
The programme consists of six core modules (120 credits) and a research project (60 credits). It comprises two stages:
- Stage 1: taught modules. There is an exit point at the end of Stage 1 (120 credits), leading to a Postgraduate Diploma. In addition, there is a possible exit award after completion of 60 credits leading to a Postgraduate Certificate
- Stage 2: Research Project
Core Modules for Year One
- Biocomputing and Big Data Handling
- Modelling
- Case Study
- Systems and Predictive Biology
- Bioinformatics
- Big Data Science
- Research Project
How Will I Be Assessed?
You will be assessed through a combination of assessment of practical skills, coursework, reports, presentations and a research project (= dissertation; 8,000–10,000 words). Assessments are designed to reinforce and stimulate the learning process in a bespoke and varied manner. They may take the form of coursework (designing bioinformatic flows, statistical analysis of data sets, model exploration for a given biological problem, critical review of a scientific paper, podcasts, code repository etc), poster presentations, portfolios and online assessments.
All assessments may be submitted through the medium of Welsh as determined by the Higher Education Welsh Language Standards. The School of Biosciences has an established record of marking Welsh-language assessments internally, or if necessary, via qualified translation services. This process is supervised by the School's Welsh Language Liaison Officer.
Program Outcome
What are the Learning Outcomes of this Course/Programme?
The Learning Outcomes for this Programme describe what you will be able to do as a result of your study at Cardiff University. They will help you to understand what is expected of you.
The Learning Outcomes for this Programme can be found below:
Knowledge & Understanding
On successful completion of the Programme you will be able to:
- Perform a rigorous hypothesis-driven approach to biological big data and recommend an appropriate experimental design for future data collection
- Translate complex and entangled biological systems into tractable mathematical and computational models
- Relate ‘omics’ approaches to mechanistic models and derive understanding
Evaluate biological problems at different scales – from molecular and cellular, to ecosystems.
Intellectual Skills
On successful completion of the Programme you will be able to:
- Compare and contrast different hypotheses and models analytically
- Apply independent learning strategies to emerging theories, technologies and software
- Use innovative approaches to analytic problem-solving
- Critically appraise and modify different emerging modelling formalisms to biological challenges
Professional Practical Skills
On successful completion of the Programme you will be able to:
- Employ advanced numeracy and computer programming to a wide spectrum of data-driven problems
- Communicate effectively and confidently through scientific writing and presentation
- Plan, design, and optimise scripting solutions
- Critically evaluate informatics workflow described in reports and papers
Judge the validity of biological conclusions drawn from large data sets.
Transferable/Key Skills
On successful completion of the Programme you will be able to:
- Lead and support “open biology” best practices
- Effectively work in interdisciplinary teams
- Design and coordinate pipelines to facilitate high-volume analyses
- Select and evaluate open-source software appropriate for specific data processing
- Use presentation skills to communicate effectively with diverse audiences using different media
- Apply data visualisation methods to data presentation and communication strategies
- Appraise and combine key concepts in bioinformatics into state-of-the-art algorithms
Program Tuition Fee
Career Opportunities
Our MSc offers excellent, broad-spectrum training for the future systems biologist. As well as becoming technically adept, you will be able to consider biological implications and hypotheses, derive predictions, and efficiently engage in modelling-data-experiment cycles. The programme will therefore prepare you for the future of predictive biology in different contexts from developmental biology to disease and ecology, as well as equipping you with the skills to excel in any industrial-based research working with big data. Its blend of theory and practical research skills, solid fundaments of dynamical systems and theoretical biology will arm you with the scientific knowledge, hands-on experience and adaptability that are highly valued by employers in today’s global job market.
In particular, we expect many of our graduates to enjoy successful careers in interdisciplinary research, in both academia and the private sector. With its focus on practical training in subject-specific and generic research skills, our programme provides the ideal platform for further study and a career in academia. During the course, many of the modules’ coursework will also emphasise how to translate science for a variety of audiences, opening other possible exciting avenues, such as scientific editing and public engagement.
Alongside the focus on biological systems, you will develop transferable skills in high demand in applied sciences, and vital in a range of roles across the public, private and third sectors. These skills include data management, curation, analysis and literacy; computational modelling; data visualisation methods; making complex research accessible to a wide audience; scripting and documenting complex computational pipelines; managing and interpreting visual data; and generating and testing hypotheses using both simple mathematical models and large data sets.
You will be part of an active research environment where novel ideas and methods can be tested and explored with the aim of deriving new biological insights. You will have access to world-leading academics with a range of expertise, who are committed to helping guide you through any interdisciplinary challenge. This environment will prepare you for your post-university career, and you will be part of a growing network that will maximise future opportunities in whichever direction you wish to pursue.
Program delivery
How Will I Be Taught?
Teaching strategies are custom-designed to meet the specific challenges of each module. You will be taught using a combination of lectures, small-group seminars and hands-on computer workshops.
Many of the modules will use flipped-learning strategies, to maximize hands-on learning, and support individual strengths and weaknesses. In flipped learning, lectures are pre-recorded and made available to you to absorb the information before our face-to-face contact time. During our live sessions, we will work together to better understand the concepts, and to apply and actively explore them through a series of activities. You will be encouraged to engage in open discussion and take the lead in organising scientific dialogue in different formats. Due to the interdisciplinary nature of the programme, these activities stimulate team building and group problem-solving using the specific strengths of each group member.
Programming skills and the use of relevant software packages will be taught (or developed) in our dedicated computer suites. To support students joining us without the required level of computational knowledge, we will provide background material regarding operating system usage and basic knowledge of the programming package R in advance of the course. The teaching staff are prepared to help you gain any IT skills needed to engage with the syllabus effectively - we will actively encourage student-led enquiries and run additional computational support sessions when necessary. An important element of the course is that continuous technical learning takes place while exploring fundamental biological and dynamical systems concepts.
You will be encouraged to attend our School seminar series with the opportunity to interact directly with the speakers and, on some occasions, to help propose which scientists to invite. Dissertation projects are designed for you to apply your knowledge to an open-ended research project. Both the choice of the project topic for the ‘Case Study’ module and the dissertation topic will be supported by “speed-dating” sessions, in which potential supervisors will briefly describe the data set and type of questions they would like to see addressed. Please see the Placement Opportunities for further details.