Taught course

Machine Learning in Science

University of Nottingham · School of Physics and Astronomy

Entry requirements

A 2.1 (or international equivalent) in one of the following areas: physics, mathematics, computer science, chemistry, engineering. A 2.2 (or international equivalent) may be considered if the applicant has relevant work experience or another supporting factor.

IELTS: 6.5 with at least 6.0 in any element.

Months of entry


Course content

In the last few years, the development and use of machine learning and artificial intelligence (AI) have revolutionised areas such as computer vision, speech recognition and natural language processing, transforming them from almost intractable problems into useful aspects of our everyday lives.

AI is also fast becoming essential in science for analysing and classifying large sets of data coming from ever more numerous observations and complex experiments. At the same time, the growing interest in the use of machine learning methods has led to new approaches to AI by applying the ideas and techniques of physical sciences which offer distinct and complementary perspectives to those of computer science and software engineering.

The interplay between AI and scientific thinking is central to the spirit of this course. It will provide you with high-quality training, covering the basic theory of machine learning with particular emphasis on the application to real science problems in the form of research projects.

The training in the application of machine learning and AI techniques to problems of scientific relevance helps build the skills that are sought after in research and in industry, enhancing your employability in a rapidly expanding area.

This MSc is aimed at students with an undergraduate degree in one of the following subjects: physics, chemistry, mathematics, computer science or engineering.

Qualification, course duration and attendance options

  • MSc
    full time
    12 months
    • Campus-based learningis available for this qualification

Course contact details

Postgraduate Enquiries
+44 (0)115 951 5559