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Artificial Intelligence for Drug Discovery at Queen Mary University of London - UCAS

Course options

2025 - 2026
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There are other course options available which may have a different vacancy status or entry requirements – view the full list of options

Course summary

Artificial Intelligence is revolutionising drug discovery, allowing us to develop better medicines faster. This MSc will teach you essential concepts of drug discovery and artificial intelligence. Through intensive training, you'll develop the advanced computational skills required to apply AI techniques to drug discovery. This programme is ideal for Chemistry graduates or a related discipline looking to pursue a career in this rapidly growing field. Programme Highlights

  • This is one of the first programmes in the world to focus on the applications of AI in Drug Discovery.
  • You will develop advanced computational and programming skills with exposure to state-of-the-art applications and languages such as Python, TensorFlow, DeepChem and Alphafold.
  • No prior knowledge of programming is assumed, making this ideal for graduates from Chemistry or a related discipline who would like to specialise in the applications of AI in Drug Discovery.
  • Chemistry at Queen Mary is currently ranked 8th in the UK (REF 2021) for its research impact. You’ll learn from world-leading researchers in computational chemistry.
Career Outcomes This programme is excellent preparation for a career in drug discovery and development. You will be well placed for roles such as:
  • Computational Drug Discovery Scientist
  • AI Research Scientist
  • Computational Chemist
  • Data Scientist
The computational skills developed can also be applied to a wide range of sectors and industries. Graduates will also be well-equipped for further research and may be interested in Queen Mary's AI for Drug Discovery Doctoral Training Programme.

Modules

Semester 1 Fundamentals of Medicinal Chemistry Scientific programming for drug discovery Molecular modelling for drug discovery Semester 2 Computational ligand-based drug discovery Data-driven drug discovery Fine-tuning lead compounds Semesters 1 and 2 Machine and Deep Learning Semesters 2 and 3 Project - Artificial Intelligence for Drug Discovery

How to apply

International applicants

Please check the course page on the Queen Mary website for information on English Language Requirements and Visas.

Entry requirements

A good 2:2 or above at undergraduate level in Chemistry, Pharmaceutical Chemistry, Medicinal Chemistry, Biochemistry, Pharmacy, Biomedical Sciences or a related discipline.

Fees and funding

Tuition fees

No fee information has been provided for this course

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

Students enrolling on a postgraduate degree programme are charged tuition fees each year by Queen Mary. The rate you will be charged depends on whether you are assessed as a Home/EU or Overseas student. You can find tuition fees for each course on the course finder pages on our website by clicking the apply link, or navigate here: https://www.qmul.ac.uk/postgraduate/ Further details about postgraduate taught tuition fees can also be found on our website: https://www.qmul.ac.uk/postgraduate/taught/tuitionfees/

Sponsorship information

To learn more about funding and scholarships, please visit our Funding a Masters webpage at: qmul.ac.uk/postgraduate/taught/funding_masters

Artificial Intelligence for Drug Discovery at Queen Mary University of London - UCAS