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  • DeadlineStudy Details: 12 months, full-time

Masters Degree Description

The future of chemistry is resilient, digitally enhanced, multidisciplinary and globally connected. Digital technologies, including data science, will enable chemical sciences researchers to see further and go faster, working seamlessly across disciplinary and international boundaries. Having tools such as these at our disposal will herald in a new era of discovery, and one which promises to deliver bigger and more significant improvements to the world we live in.

You’ll benefit from high-quality teaching from across two Departments in the Faculty of Science:

the Department of Pure & Applied Chemistry
the Department of Computer & Information Sciences
Graduates of this course will have excellent employment opportunities for multi-disciplinary data science jobs.

Entry Requirements

Minimum second-class (2:2) Honours degree, or international equivalent, in a relevant subject such as Chemistry, Computing Science, Chemical Engineering, Mathematics, Physics or closely related subject.

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Fees

See our website for fees

Student Destinations

The MSc Chemistry with Data Science is specifically designed to produce graduates who are skilled in the traditional fields of chemistry with expertise in the increasingly data-driven world of science and industry.

This innovative degree programme will equip you with a unique skill set that is in high demand across various STEM sectors, including:

the pharmaceutic industry
materials science
environmental science
manufacturing
regulatory roles
Our graduates are also in a strong position to pursue further academic career as PhD researchers in a variety of cross-disciplinary projects.

Module Details

Python 101 for Chemists (20 credits)
Computational Chemistry (10 Credits)
Legal, Ethical and Professional Issues for the Information Society (10 credits)
Big Data Tools & Techniques (10 credits)
AI & Machine Learning (10 credits)
Software Engineering & High Performance Computing (10 credits)
Time Series Analysis for Chemistry (10 credits)
Scientific Research Methods (10 credits)
Machine Learning for Data Analytics (20 Credits)
Research Project (60 credits)

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