Plastic bottles, contact lenses, shampoo, paint, and even the proteins in your body all belong to a class of materials called soft matter, and a new national training centre will produce the next generation of scientists who understand how these substances behave. The problem is that UK industries making everything from food to pharmaceuticals to coatings cannot find enough PhD-trained researchers who understand the full breadth of soft matter science. Companies typically need people who can work across polymers, colloids, and complex mixtures simultaneously, but most doctoral training has been narrowly focused on just one area. These industries account for 17.2% of UK GDP and employ over 1.1 million people. The Centre for Doctoral Training will train 16 PhD students per year in both fundamental blue-skies science and industry-embedded applied research. Industrial partners—with combined annual revenues of nearly £200 billion—have already indicated they could hire three times the annual cohort. If successful, the centre will fill a critical skills gap, ensuring that UK manufacturing sectors can continue to develop better products, from more effective medicines to longer-lasting paints, without having to recruit talent from abroad.
View original technical description
Soft matter and functional interfaces are ubiquitous! Be it manufactured plastic products (polymers), food (colloids), paint and other decorative coatings (thin films and coatings), contact lenses (hydrogels), shampoo and washing powder (complex mixtures of the above) or biomaterials such as proteins and membranes, soft matter and soft matter surfaces and interfaces touch almost every aspect of human activity and underpin processes and products across all industrial sectors - sectors which account for 17.2% of UK GDP and over 1.1M UK employees (BIS R&D scoreboard 2010 providing statistics for the top 1000 UK R&D spending companies). The importance of the underlying science to UK plc prompted discussions in 2010 with key manufacturing industries in personal care, plastics manufacturing, food manufacturing, functional and performance polymers, coatings and additives sectors which revealed common concerns for the provision of soft matter focussed doctoral training in the UK and drove this community to carry out a detailed "gap analysis" of training provision. The results evidenced a national need for researchers trained with a broad, multidisciplinary experience across all areas of soft matter and functional interfaces (SOFI) science, industry-focussed transferable skills and business awareness alongside a challenging PhD research project. Our 18 industrial partners, who have a combined global work force of 920,000, annual revenues of nearly £200 billion, and span the full SOFI sector, emphasized the importance of a workforce trained to think across the whole range of SOFI science, and not narrowly in, for example, just polymers or colloids. A multidisciplinary knowledge base is vital to address industrial SOFI R&D challenges which invariably address complex, multicomponent formulations. We therefore propose the establishment of a CDT in Soft Matter and Functional Interfaces to fill this gap. The CDT will deliver multidisciplinary core science and enterprise-facing training alongside PhD projects from fundamental blue-skies science to industrially-embedded applied research across the full spectrum of SOFI science. Further evidence of national need comes from a survey of our industrial partners which indicates that these companies have collectively recruited >100 PhD qualified staff over the last 3 years (in a recession) in SOFI-related expertise, and plan to recruit (in the UK) approximately 150 PhD qualified staff members over the next three years. These recruits will enter research, innovation and commercial roles. The annual SOFI CDT cohort of 16 postgraduates could be therefore be recruited 3 times over by our industrial partners alone and this demand is likely to be the tip of a national-need iceberg.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know