Assistant Professor, Faculty of Engineering
Dr Watson has a MEng in Mechanical Engineering (University of Hull, 2005) and a PhD in Chemical Engineering (University of Leeds, 2010). From 2010 to 2014 he was a Post-Doctoral Research Assistant in the School of Food Science and Nutrition at the University of Leeds. His research there was performed in the Food Physics Research Group and was funded by Innovate UK, BBSRC and via numerous industrial collaborators. In 2013 Dr Watson became a chartered engineer and he is a member of the Institute of Mechanical Engineers and an Associated Member of the Institute of Chemical Engineers. In 2013 he was also one of the founding directors of the start-up company Albion Crystallisation Ltd, who specialise in developing energy efficient food processing technology. In 2014 he was appointed as an Assistant Professor of Chemical Engineering at the University of Nottingham. In 2015 he became a fellow of the Higher Education Academy.
Dr Watson is a member of the Food, Water, Waste (FWW) Research Group.
I teach final year and MSc module related to food processing and contribute to the departments design projects.
·CHEE4061: Food Processing
· CHEE4005: Advanced Rheology and Materials
My research is focused on the optimisation of industrial processes using non-invasive sensor technology. The application of my research is primarily within the food manufacturing sector where… read more
Airborne Ultrasound for Real-time Measurement of Physical Structures
3 Year PhD fully funded studentship for Home EU students.
The world is full of multi-component products such as foods (biscuits and fruits) and automotive components (Hybrid materials). The physical structure of these products affects their performance and there is a need for methods to characterise them during manufacturing. This project will utilise a novel airborne ultrasound instrument to develop techniques to characterise these structures. Airborne ultrasound systems use high frequency sound waves such as those used for medical imaging and non-destructive testing. However, they do not require direct contact with the sample under inspection, making them suitable for industrial environments. The project will focus on how the sound propagates through these systems and how data is recorded by the instrument. State of the art machine learning algorithms will also be developed to characterise different industrially relevant multi-component structures.
Requirements of studentship:
1) Students should have, or expect to obtain, a first-class or good 2:1 honours degree, or a distinction or high merit at MSc level (or international equivalent) in Engineering, Physics, Maths or Computer Science.
2) Students should be able to demonstrate an interest in developing instruments and measurement techniques. Students with experience or a willingness to learn software such as LabVIEW and MATLAB are encouraged to apply.
My research is focused on the optimisation of industrial processes using non-invasive sensor technology. The application of my research is primarily within the food manufacturing sector where developed technology has improved process productivity and product quality.
· Ultrasonic Process Analytical Technologies
· Machine Learning and Sensor Fusion
· Industrial Internet of Things Applications
· Online Food Quality Assessment
I welcome enquiries from potential PhD candidates from Home, EU and international countries who are interested in the following research areas: Digital Food and Drink Manufacturing, Ultrasonic Process Analytical Technologies, Machine Learning and Sensor Fusion, Industrial Internet of Things Applications, Online Food Quality Assessment
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