Heriot-Watt is a leader in applied mathematics research and education. Our faculty is at the forefront of many areas, including mathematical biology and ecology, machine learning, data science, financial modelling, and more. This 2 year master's programme aims to provide students with the cutting-edge mathematical and statistical skills needed for success in today's data-driven world. Through a diverse curriculum and real-world projects, students will gain a solid theoretical foundation as well as hands-on experience applying mathematical concepts to tackle complex challenges across industries. Whether your interests lie in mathematical biology and ecology, artificial intelligence, big data analytics or other emerging fields, this programme will prepare you with the sophisticated analytical abilities and computational tools to launch an impactful career. The 2-year MSc breakdown The first year (Stage 1) of this two year MSc Programme is a pre-masters year that will equip you with a solid, theoretical and practical foundation in applied mathematics. The second year (Stage 2) is the same as our current one-year MSc Programme in Applied Mathematical Sciences which is designed to equip students with the modern, transferrable mathematical skills to prepare them for careers in industry and research. EmployabilityThe MSc in Applied Mathematical Sciences (2 years) programme prepares you to work across many industries. You will gain highly transferrable skills in mathematical modelling, data analytics, computational methods, and more.Potential career pathsData Scientist - Analyse data to uncover insights and trends to inform business strategy and decision-making.Business Analyst - Use data modelling and statistical analysis to solve problems and improve business processes.Operations Researcher - Apply mathematical optimization techniques to complex logistics and resource allocation problems.Quantitative Analyst - Build mathematical models to analyse financial markets, price assets, and quantify risk.Statistical Modeller - Develop predictive models and perform statistical inference on data.Machine Learning Engineer - Design, implement and deploy machine learning algorithms and artificial intelligence applications.Delivery type: Full Time, Part Time available