Mathematics, Artificial Intelligence, and Real-world Systems (MARS) Lancaster University

Overview

This Mathematics, Artificial Intelligence, and Real-world Systems (MARS) course from Lancaster University  begins by building upon your understanding of mathematical methods and concepts through a mix of lectures and workshops. You will explore a wide range of topics, from differential equations, vector calculus, probability and statistics to logic, proofs and theorems. In addition to this, computing skills are essential, which is why you will learn the principles of scientific computing and gain experience working with the R and Python programming languages.

You will develop valuable transferrable skills such as data analysis, problem-solving and quantitative reasoning, all of which make you highly desirable to future employers. These skills are honed by working in collaboration with fellow students, ruminating on theories and testing them out, delivering presentations and communicating your research results.

Career opportunities:

As a graduate of Lancaster, you will enjoy excellent employment prospects. Your qualification in Mathematics, Artificial Intelligence and Real-world Systems (MARS), along with your problem-solving skills, analytical abilities, and AI expertise, will make you highly desirable to employers in almost every industry and sector. This includes technology and AI, finance and insurance, engineering, environmental and climate science, healthcare and biomedical research, and government. The types of roles you may progress into include data scientist, data analyst, risk analyst, climate modeller, software engineer, scientific programmer, actuary, machine learning engineer, and mathematical engineer. Many of these roles are available across multiple sectors allowing you to choose a pathway that reflects your interests.

This degree will equip you to work in a variety of global businesses in a range of fields, including, but not limited to:

• Aerospace engineering (Airbus, Boeing, BAE, NASA)

• Automotive engineering (Tesla, BMW, Mercedes-Benz)

• Software development and software engineering (Google, Apple, Microsoft)

• Robotics and automation (ABB Robotics, DENSO, KUKA)

• Cyber security (GCHQ, NCSC, Cisco)

• Climate modelling and analytics (Met Office, CEDA, Climate X)

• Bioinformatics and computational biology (The Francis Crick Institute, The Pirbright Institute, Wellcome Sanger Institute)

• Health data science (NHS, UKHSA, HDRUK)

• Medical imaging (Seimens, Philips, Canon)

• Investment banking (Barclays, Morgan Stanley, Goldman Sachs)

Your transferable skills will also allow you to expand into roles in marketing, management, and consultancy.