Postgraduate study
Gain advanced training into the fundamentals of modern machine learning and artificial intelligence with particular focus on their application to problems across the sciences.
 
  
Qualification
MSc Machine Learning in Science
Duration
1 year full-time
Entry requirements
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 (no less than 6.0 in any element). If these grades are not met, English preparatory courses are available

If these grades are not met, English preparatory courses may be available
Start date
September
UK/EU fees
£7,290 - Terms apply
International fees
£21,285 - Terms apply
Campus
University Park Campus
School/department

Physics and Astronomy

 

 

Overview

In the last few years the development and use of machine learning (ML) 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 ML 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.

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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 ML with particular emphasis on the application to concrete science problems in the form of research projects.

The training in the application of ML and AI techniques to concrete 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.

 

Full course details

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

This one-year course consists of 180 credits, split into 120 credits of taught modules during the autumn and spring semesters, and a 60-credit research project that is completed in the summer period.

Modules are delivered through lectures and problem classes. There are a wide range of core compulsory modules and optional modules, as well as three alternative strands which allow you to select core and optional modules in different combinations. This allows you to choose modules to fit your undergraduate background and personal interests.

Research project

During the summer period, you will concentrate on an independent research project which focuses on the application of machine learning methods, to original scientific problems provided by research groups from across the Faculty of Science. The project involves writing a dissertation and is supervised by a member of the academic staff.

 
 

Modules

You will study the following core modules:

  • Machine Learning in Science – Part one
  • Machine Learning in Science – Part two
  • Machine Learning in Science – Project

In addition, this course offers three alternative strands/pathways which allow you to select different combinations of core and optional modules to meet your interests.

Strand one core modules:

  • Machine Learning
  • Statistical Machine Learning

Strand two core modules:

  • Statistical Foundations
  • Fundamentals of Statistics

Strand three core modules:

  • Programming
  • Scientific Programming in Python

Optional modules:

  • The Physics of Deep Learning
  • Professional Ethics in Computing
  • Computer Vision
  • Quantum Information and Quantum Computing
  • Computational Neuroscience A
  • Computational Neuroscience B
  • Chemistry - in-silico
  • Big Data and Cloud Computing
  • Designing Intelligent Agents

The above is a sample of the typical modules that we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Due to the passage of time between commencement of the course and subsequent years of the course, modules may change due to developments in the curriculum and information is provided for indicative purposes only.

 
 

Fees and funding

See information on how to fund your masters, including our step-by-step guide. Further information is available on the school website.

As a student on this course, we do not anticipate any extra significant costs, alongside your tuition fees and living expenses. You should be able to access most of the books you’ll need through our libraries, though you may wish to purchase your own copies which you would need to factor into your budget.

 

UK/EU Students

The Graduate School website at The University of Nottingham provides more information on internal and external sources of postgraduate funding.

International and EU students

The University of Nottingham offers a range of masters scholarships for international and EU students from a wide variety of countries and areas of study.

Applicants must receive an offer of study before applying for our scholarships. Please note the closing dates of any scholarships you are interested in and make sure you submit your masters course application in good time so that you have the opportunity to apply for them.

The International Office also provides information and advice for international and EU students on financing your degree, living costs, external sources of funding and working during your studies.

Find out more on our scholarships, fees and finance webpages for international applicants.  
 

Careers and professional development

Machine learning and artificial intelligence have become central for the economy and society. Graduates with expertise in this area are highly sought after in all sectors that are data intensive, including IT, finance, consultancy, manufacturing, and large areas of academic and industrial research and development.

Average starting salary and career progression

In 2017, 87.5% of postgraduates in the school who were available for employment had secured work or further study within six months of graduation. The average starting salary was £30,000 with the highest being £31,000.*

* Known destinations of full-time home postgraduates 2016/17. Salaries are calculated based on the median of those in full-time paid employment within the UK. 

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Career Prospects and Employability

The University of Nottingham is consistently named as one of the most targeted universities by Britain’s leading graduate employers* and can offer you a head-start when it comes to your career.

Those who take up a postgraduate research opportunity with us will not only receive support in terms of close contact with supervisors and specific training related to your area of research, you will also benefit from dedicated careers advice from our Careers and Employability Service.

Our Careers and Employability Service offers a range of services including advice sessions, employer events, recruitment fairs and skills workshops – and once you have graduated, you will have access to the service for life.

* The Graduate Market 2013-2016, High Fliers Research..

 
 

Related courses and downloads

 

Disclaimer
This online prospectus has been drafted in advance of the academic year to which it applies. Every effort has been made to ensure that the information is accurate at the time of publishing, but changes (for example to course content) are likely to occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for the course where there has been an interval between you reading this website and applying.

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