The University of Strathclyde has launched an MSc in Advanced Mathematical Modelling, a program designed for students with a strong mathematical background. This course equips graduates with advanced problem-solving skills, enabling them to tackle real-world challenges across various industries and research fields. The MSc in Advanced Mathematical Modelling provides a comprehensive foundation in: Mathematical Biology Continuum Mechanics Optimisation Numerical Methods Students will gain hands-on experience developing and analysing models for applications in climate science, fluid dynamics, medical research, and engineering design. Life in a Foreign University | ‘Beyond academics, my time at Sheffield University was defined by experiences that shaped me’ A webinar will be held on May 15, 2025, at 13:00 BST, offering an overview of the programme and a Q&A session with faculty and the admissions team. Course Structure & Research Opportunities Semesters 1 & 2: Flexible module selection, including deep learning, finite element methods, and optimisation. Semester 3: An individual research project, allowing students to apply mathematical modelling to industry-relevant or research-focused problems in engineering, finance, and science. Dr. Alexander Wray, Programme Director, said: "This MSc addresses the global demand for mathematically skilled graduates capable of tackling real-world problems with creativity and precision—whether in disease modelling, climate dynamics, or complex fluid simulations." Entry Requirements & Scholarships Minimum Second-Class (2:2) Honours Degree (or equivalent) in Mathematics, Computer Science, or a related discipline with a strong mathematical component. A candidates with relevant professional experience will be considered. English Language Requirement: IELTS 6.0 (no component below 5.5). International student fee: £25,500. Scholarships Available: 850 Glasgow International Masters Scholarships worth £5,000 each for September 2025 intake. Career prospects Graduates will be well-prepared for roles in engineering, finance, risk modelling, data science, machine learning, energy, environmental modelling, and healthcare research.
