COURSE CURRICULUM

The taught stage of the MSc Digital Chemical Engineering programme at Aston University provides a 105-credit core curriculum supported by a 15-credit optional machine learning module, designed to develop advanced expertise in digital tools, sustainable process design, and modern chemical engineering practice. Aston Global Advantage runs throughout the programme and focuses on professional development, leadership, communication, teamwork, and employability skills that support career readiness in industry and research. Engineering Project Management develops students’ ability to plan, organise, and deliver complex engineering projects, covering risk management, scheduling, resource allocation, and multidisciplinary coordination. Life Cycle Analysis and Circular Economy introduces sustainability assessment methods, enabling students to evaluate environmental impacts of chemical processes and design systems aligned with circular economy principles. The Interdisciplinary Design Project allows students to work collaboratively on complex engineering challenges, integrating knowledge from multiple disciplines to design innovative and practical solutions. Smart Sensors and Control Systems explores modern instrumentation, automation, and control technologies used in chemical engineering processes, enabling real-time monitoring, optimisation, and improved system performance. Digital Process Engineering focuses on computational modelling, simulation, and data-driven approaches to designing and improving chemical and biochemical processes using digital technologies. Sustainable Chemical and Biochemical Engineering Design develops advanced skills in designing efficient, environmentally responsible chemical and biochemical systems with a strong emphasis on decarbonisation, renewable resources, and sustainable industrial practices. To complement these core areas, students choose one optional module in machine learning, selecting either Applied Machine Learning (Python-based) or Machine Learning (MATLAB-based), depending on prior technical background. This module strengthens students’ ability to apply predictive modelling and data analysis techniques within engineering contexts. Together, these modules provide a strong blend of digital engineering, sustainability, process design, and data science, preparing graduates for careers in chemical engineering, process optimisation, energy systems, sustainable manufacturing, and digital transformation roles within industry and research environments.