MSc Artificial Intelligence and Machine Learning in Science
Mile End Campus (Main), United Kingdom
MSc Artificial Intelligence and Machine Learning in Science
Queen Mary University of London
Artificial Intelligence & Machine Learning
Program Overview: MSc AI and Machine Learning in Science
The MSc Artificial Intelligence and Machine Learning in Science at Queen Mary University of London is a cross-disciplinary programme that teaches you the fundamentals of AI and machine learning, with a strong focus on applying these techniques to real-world scientific problems. From climate change and drug discovery to particle physics, you will develop the coding and programming skills required to harness AI across a wide range of scientific fields.
Core compulsory modules cover probability, statistics, machine learning, and deep learning, providing you with a solid foundation in AI. You will also gain hands-on experience with leading tools and programming languages such as R, Python, C++ and SQL, working with real datasets from prestigious research organisations including CERN, NASA, and LIGO.
No prior programming experience is required, making this programme accessible to graduates from a broad range of STEM backgrounds. You will collaborate closely with Queen Mary researchers on a research project, applying your AI and machine learning skills to high-profile datasets in areas such as computational chemistry, epidemiology, renewable energy, and more.
Key Program Highlights
- Work with real datasets from leading research organisations such as CERN, NASA, and LIGO
- Learn from expert academics including Turing Fellows and members of the Digital Environment Research Institute (DERI)
- No prior programming experience required, with accessible entry for all STEM graduates
- Complete a research project applying AI and ML skills to active scientific research areas
Curriculum & Modules
The programme comprises three compulsory modules and four elective modules, culminating in a substantial research project in Data Science. Modules are taught through a combination of lectures, seminars, and computer lab sessions, with the Machine and Deep Learning module spanning both semesters to ensure thorough coverage of core concepts.
This module establishes the probability and statistics background required for applying advanced AI techniques. It covers essential theoretical notions of probability, distributions of random variables, and various types of statistical hypothesis tests.
A two-semester core module covering the principles and practice of machine learning and deep learning. You will develop the theoretical understanding and practical skills to implement and evaluate a range of ML and DL algorithms for scientific applications.
Designed to help you attain the relevant skills to assess, understand, and visualise data for your research project. This includes communication skills, organising information from the literature, extracting data science methods from a multidisciplinary environment, and report writing.
A major individual research project where you work on topics in AI and Machine Learning in Science set by your project supervisor. Computational work is the principal component, alongside critical evaluation of previously published results and preparation of a dissertation.
An elective module exploring the mathematical and computational methods for analysing time-dependent data. You will study forecasting, trend detection, and pattern recognition techniques applicable to scientific datasets.
Elective Module Areas
Admission Requirements
This programme welcomes applicants from a range of STEM backgrounds, and no prior programming experience is required. To be considered for admission, you should meet the academic and language requirements outlined below. Contact Uni4Edu for personalised guidance on your eligibility and application.
Academic Requirements
- Undergraduate DegreeA good 2:2 or above at undergraduate level in Mathematics, Physics, Chemistry, Computing, Engineering or any other STEM subject
- Programming ExperienceNo prior programming experience required
- International QualificationsEquivalent international qualifications are accepted; contact Uni4Edu for country-specific requirements
- Work ExperienceNot required, though relevant experience in a scientific or technical field is beneficial
- Personal StatementA statement demonstrating your interest in AI and machine learning applications in science
English Language Requirements
- IELTSContact Uni4Edu for the latest score requirements
- TOEFL iBTContact Uni4Edu for the latest score requirements
- PTE AcademicContact Uni4Edu for the latest score requirements
Required Documents
For personalized admission guidance, document verification, and application support, please contact Uni4Edu
Scholarships & Funding
Queen Mary University of London offers a range of scholarships to support international postgraduate students. These merit-based and region-specific awards can significantly reduce the cost of your studies. Contact Uni4Edu for full details on eligibility and how to apply for funding.
President's Global Scholarship
GBP 10,000Available to highly qualified postgraduate taught offer holders from South Asia and other eligible regions. This prestigious award recognises outstanding academic achievement and is applied as a tuition fee reduction.
Global Excellence Scholarship
GBP 7,000Designed for high-achieving international postgraduate taught offer holders. This scholarship rewards academic excellence and is available for eligible programmes across the university.
Global Talent Scholarship
GBP 5,000Open to high-achieving international students holding an offer for a full-time masters programme with overseas fee status. The scholarship is applied as a deduction from tuition fees upon enrolment.
For detailed tuition fee information, please contact Uni4Edu — we will guide you through the costs and available funding options for this program.
Career Prospects
The demand for qualified AI and Machine Learning experts is growing rapidly, with an explosion of AI opportunities in London and beyond. From environmental science to healthcare, finance to retail, organisations are seeking skilled graduates with hands-on coding and programming skills. The broad scope of this MSc and its focus on developing strong theoretical and practical skills positions you for a wide range of career paths.
Potential Career Roles
Sectors and Employers Hiring Graduates
Rankings & Recognition
Queen Mary University of London is a member of the prestigious Russell Group of research-intensive UK universities and has demonstrated consistent upward momentum in global rankings. The university is recognised for the quality of its research and its diverse, globally connected campus community in the heart of London.
| Subject | Ranking Body | Rank |
|---|---|---|
| Artificial Intelligence & Data Science | QS Subject Rankings | Top 100 in the World / 8th in the UK |
| Computer Science & Engineering | THE Subject Rankings | 126-150 globally |
| Mathematics | QS Subject Rankings | Top 100 globally |
| Research Quality (UK) | Complete University Guide | #16 in the UK |
How to Apply
Applying for this program is easy with Uni4Edu. Our team will guide you through every step of the process — from document preparation to final enrolment.
Contact Uni4Edu
Reach out to our team via email or phone. We will assess your profile and confirm your eligibility for this program.
Prepare Your Documents
Our advisors will provide you with a personalised checklist of required documents and help you prepare your application package.
Submit Your Application
Uni4Edu will submit your application on your behalf and keep you updated on its progress throughout the review period.
Receive Your Offer
Once accepted, we will help you understand your offer, arrange visa support if needed, and guide you through the enrolment process.
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