This exciting project constitutes a collaboration with the health and hygiene Industry and entails a holistic engineering systems approach towards achieving sustainability targets specific to the industry, but which can be useful in a broader industrial context under the Industry 4.0 objectives.
The project will include the construction of detailed process models based on a combination of fundamental principles and data-driven approaches, and machine learning (ML) techniques using historical data directly form the industrial processes. Novel methodologies for multi-level and real-time optimisation (RTO) will be subsequently developed based on the ambitious sustainability targets the for health and hygiene Industry. The project is expected to develop new technological solutions at different steps of the whole supply chain. It will combine modelling, optimisation, optimal control, sustainability analysis, together with laboratory testing and analytical techniques. A number of technological advances both sector-specific and more general are expected to emerge.
The successful candidate will work in close collaboration with the industrial partner and will be an integral part of the company’s industrial development. Computational experience in terms of computer programming, modelling and optimisation techniques is essential. Understanding sustainability from a holistic point of view is critical for the success of the project. A good process understanding in an industrial context and industrial experience is also desirable.
The project is expected to start in July or September 2021 in agreement with the industrial sponsor.
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.
We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).
All appointments are made on merit.