Data Science and Industrial Biotechnology MSc

Important application information

This course is still subject to full university approval and is due to start in September 2026. The information given below is intended for guidance purposes only and may change once the course is fully approved.

Please fill in our online form. We'll use this to let you know when:

• the course gets full university approval
• more in-depth course information becomes available
• we can start accepting applications

Overview

Biology is at the heart of society’s grand challenges, from food security and global health to biodiversity loss and climate change. Addressing these complex issues increasingly relies on data-driven solutions.

As bioscience industries undergo rapid digital transformation, a skills gap has emerged in data handling, modelling, and interpretation. Our Data Science and Industrial Biotechnology MSc is designed to close this gap.

We will prepare you for a career at the cutting-edge of industrial biotechnology, bioinformatics, environmental monitoring, or health innovation.

During your studies, you’ll learn how to turn complex biological and environmental data into meaningful insights. You’ll work with genuine datasets to solve authentic challenges, from modelling microbial communities to predicting bioprocess yields.

You’ll be taught by leading academics from our Centre for Industrial Biotechnology. Our researchers are at the forefront of applying data science to real-world biological challenges. This ensures your learning is shaped by pioneering science and industry insight.

What sets our course apart is the strong connection to industry. You’ll work on live project briefs, co-designed hackathons, and applied assessments that mirror real-world practice. You’ll graduate with a portfolio that showcases actual skills to future employers.

Aspects of this course are delivered by expert data scientists from the UK’s National Innovation Centre for Data (NICD). You’ll immerse yourself in their leading-edge techniques, practical implementation, and ethical considerations of data science. NICD will help you learn with data bootcamps and learning through experience.

Whether you are looking to transition into data science or apply it more effectively in a life sciences context, this course is well suited. The programme will equip you with the practical, analytical, and professional expertise employers are looking for.

Important information

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Your course and study experience - disclaimers and terms and conditions

Please rest assured we make all reasonable efforts to provide you with the programmes, services and facilities described. However, it may be necessary to make changes due to significant disruption, for example in response to Covid-19.

View our Academic experience page, which gives information about your Newcastle University study experience for the academic year 2025-26.

See our terms and conditions and student complaints information, which gives details of circumstances that may lead to changes to programmes, modules or University services.

 

Additional information

Who this course is for

This MSc is ideal for graduates looking to transition into data science but have an interest in biotechnology.

Applicants should not have a degree in computer science or a course with significant computational content.

The programme is particularly suited to those interested in applying data science techniques in bioscience and industrial biotechnology contexts. This MSc offers a structured, supportive route into data-driven roles with real-world impact, whether you aim to work in:

• sustainable manufacturing
• digital health
• environmental analysis, or
• research and development

What you'll learn

Phase one: Core foundations in Data Science

In phase one, you’ll build a solid foundation in:

• programming
• statistics
• machine learning
• data handling and visualisation.

You will develop confidence in using tools such as R, Python, and Jupyter.

Once you’ve mastered these core skills, you’ll explore the theory and applications of data science in greater depth. In a module delivered by the UK’s National Innovation Centre for Data (NICD), you’ll work on solutions to real challenges drawn from NICD’s client projects.

You’ll also develop your legal skills, ensuring you’re up to date with:

• legal frameworks
• data protection, privacy and security
• equality and non-discrimination

Phase two: Data Science and Industrial Biotechnology

In phase two, you’ll apply your data science skills to industrial bioscience applications.

You’ll learn to retrieve, curate, and harmonise biological and environmental data from public sources. You’ll then apply statistical and machine learning techniques to genuine datasets. You’ll develop workflows to support industrial research challenges such as bioprocess optimisation, metagenomics, and AMR prediction.

Phase 3: Capstone project

In phase three, you’ll complete a three-part capstone project that mirrors the full research and innovation cycle:

• Part 1: Research project preparation
• Part 2: Individual data science project based on a group-defined theme
• Part 3: Group hackathon co-delivered with industry partners

This final phase allows you to apply your skills in authentic industrial or research contexts, creating a portfolio that showcases your employability for data-driven bioscience roles.

Modules

You will study modules on this course. A module is a unit of a course with its own approved aims and outcomes and assessment methods.

Course content changes

Module information is intended to provide an example of what you will study.

Our teaching is informed by research. Course content changes periodically to reflect developments in the discipline, the requirements of external bodies and partners, and student feedback.

Full details of the modules on offer will be published through the Programme Regulations and Specifications ahead of each academic year. This usually happens in May.

To find out more please see our terms and conditions.

Optional modules availability

Some courses have optional modules. Student demand for optional modules may affect availability.

 

How you'll learn

Delivery and teaching methods

You’ll be taught using a range of methods, including:

• lectures and seminars
• interactive workshops combining short lectures with hands-on coding exercises
• computer-based practical sessions using R, Python, and Jupyter
• data ‘bootcamps’
• flipped learning
• project-based group work on genuine bioscience datasets
• supervised independent research and collaborative problem-solving
• peer review and formative feedback sessions
• industry co-delivered hackathon challenge
• guided independent study

Assessment methods

Depending on your modules, you'll be assessed through a combination of:

• Case study
• Computer assessment
• Dissertation
• Oral presentation
• PC examination
• Practical lab report
• Portfolio
• Problem-solving exercises
• Report
• Research proposal
• Written examination

Additional assessment information

Some assessments will be completed on our specialist software Numbas, which will test your mathematical knowledge.

Support

Data Science resources

Before the course begins, you’ll receive a set of resources designed to support your transition into data science. These materials provide a fast-paced refresher on key mathematical concepts, helping bridge the gap between what you learned at school and what you'll encounter on the course. You’ll start your course with confidence and be able to refer to the resources as your learning progresses.

Numbas learning software

You'll have access to specialist learning software called Numbas. Developed at Newcastle University, it's now used by mathematicians and statisticians worldwide. This innovative software allows you to work on interactive code worksheets, enabling you to test and refine the mathematics skills you’ll need for data science.

Maths-Aid

All students on our Data Science conversion degrees can make use of Maths-Aid, a team of experts who provide support and advice on all aspects of maths and statistics.

Statistics and Data Science clinic

During your capstone project, you’ll be supported by our Statistics and Data Science Clinic, where you can book one-to-one sessions with our expert data scientists. Whether you need support with a technical

Our staff

This course is delivered by:

• School of Mathematics, Statistics and Physics
• School of Computing
• School of Natural and Environmental Sciences

You'll be taught by experts working at the frontier of data science. You'll work alongside academics from the following research areas:

• Centre for Data Science and AI: Driving the development and application of new methods for extracting the value from data
• Statistics and Data Science: World-class research in modern statistics and data science.
• Scalable Computing: Internationally renowned for tackling research challenges in high performance systems, data science, machine learning and data visualization.
• Centre for Industrial Biotechnology: Sustainably harnessing the power of natural processes.
• Molecular Life Sciences: Investigating the molecular biology and biochemistry of plants, microbes, and invertebrates.

We're home to the UK’s National Innovation Centre for Data (NICD). This gives you unique opportunities to collaborate with industry partners across multiple sectors.

Your development

Professional skills

Through a module delivered by the National Innovation Centre for Data (NICD), you’ll develop key professional skills by working through genuine innovation processes. You’ll take a problem from initial formulation through to a practical, client-focused solution.

You’ll also strengthen your project management, teamwork and communication skills by working on a group project and learning how to present your complex data to non-specialist audiences.

Research skills

You’ll learn to design, implement, and report on data-driven research projects. This includes:

• formulating hypotheses
• selecting appropriate analytical methods
• evaluating models
• interpreting findings in a biological context

The capstone project provides extensive experience in independent and team-based inquiry.

Practical skills

You’ll become proficient in coding with R and Python, using tools such as Jupyter and R Markdown to develop reproducible workflows. You’ll work with genuine datasets, learning to source, clean, integrate, and analyse data from public bioscience databases and industrial case studies.

Work experience opportunities

Although this course doesn’t include a formal placement, you’ll gain practical experience through project-based learning using real-world industrial scenarios. The final group hackathon is co-delivered with industry partners, allowing you to work on live briefs and engage directly with employers.

There are a number of opportunities to secure work experience and placements with support from our Careers Service.

Your future

Your career

The course prepares you for a wide range of careers in roles that bring together life sciences and data science, which might include:

• bioinformatics analyst
• bioprocess data scientist
• environmental data scientist
• microbial genomics researcher
• industrial R&D data consultant
• agritech or synthetic biology analyst

You’ll graduate with a portfolio of applied work that showcases your technical skills, biological understanding, and ability to deliver data-led solutions.

You’ll be prepared to work in a variety of industries, including:

• industrial biotechnology and biomanufacturing
• pharmaceutical and healthcare companies
• health and environment agencies
• data consultancy and scientific software development
• agritech and environmental sustainability firms
• academic and commercial research labs
• food and bioenergy production
• regulatory and quality assurance bodies

This course builds on those pathways with a stronger focus on industrial application and technical fluency.

Further study

This course provides a strong foundation for PhD-level research in areas such as:

• bioinformatics
• microbial genomics
• environmental data science
• biotechnology

The structured dissertation pathway equips you with the critical and technical skills needed for advanced academic study.

Industry links

We have strong industry links through our research collaborations and curriculum design. Our industrial partners help shape assessment briefs, contribute to group projects, and co-deliver the final hackathon challenge. These relationships provide you with:

• exposure to real-world data challenges and workflows
• insights into emerging sector priorities
• networking opportunities with potential employers

Industry collaborators have included:

• Procter & Gamble
• Northumbrian Water
• Ginkgo Bioworks
• Lonza
• others across environmental and biotech sectors

Our Careers Service

Our Careers Service is one of the largest and best in the country, and we have strong links with employers. 

Visit our Careers Service website

Facilities

The School of Computing also has a state-of-the-art data visualization lab which may be used for project work. It includes:

• £250,000 stereoscopic wall display
• large touchscreen display
• eye trackers
• hand-tracking devices

Urban Sciences Building

The School of Computing is based in the £58 million Urban Sciences Building (USB), a flagship development located on the £350 million Newcastle Helix regeneration site in the heart of Newcastle. Newcastle Helix brings together:

• academia
• the public sector
• communities
• business and industry

The USB is a living laboratory and has over 4,000 sensors that record detailed research data, which can be used in student projects.

As a student, you'll have access to facilities including:

• 300+ PCs with a Raspberry Pi3 on every desk
• large, flexible computer clusters
• collaborative spaces for study or group projects
• dedicated practical space for postgraduate students
• Urban Café

Open days and events

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