This Master's program focuses on the intersection of Artificial Intelligence (AI) and Machine Learning (ML) with scientific applications. You will gain a strong foundation in AI and ML principles and learn how to apply them to solve real-world scientific challenges across various fields like climate change, drug discovery, and particle physics. The course is designed to equip you with essential coding, programming, and mathematical skills, preparing you to work with large datasets and contribute to advancements in scientific research and industry. No prior programming experience is required to start this program.
The MSc program consists of compulsory modules covering fundamental AI concepts, machine learning, deep learning, and research methods. You will also choose elective modules to specialize in areas relevant to your interests and career goals. A significant part of the program involves an independent research project where you will apply your learned skills to a high-profile dataset or an active research area.
No programming experience is required for entry.
Fees are subject to an annual increase. Postgraduate accommodation is for 51 weeks and ranges from £6,769.53 to £12,603.38 for the 2026-27 academic year.
You need a minimum of a 2:1 undergraduate degree in a relevant scientific or mathematical discipline. No prior programming experience is required for entry.
The international tuition fee for this program is £31,450 per year. Estimated living costs are around £12,603.38 for 38.3 weeks.
This is a full-time Master's program with a duration of 1 year.
The program has an intake in September 2026.
Applications are made directly to Queen Mary University of London through their online application portal. You will need to submit academic transcripts, proof of English language proficiency if applicable, and potentially a personal statement and references.
This program prepares graduates for roles applying AI and Machine Learning to scientific challenges in research institutions, scientific industries, and technology companies, focusing on data analysis, predictive modeling, and automation.