Sebum, a waxy lipid-rich biofluid, is produced from the sebaceous gland and is traditionally connected with skin conditions such as acne1, psoriasis2 and seborrhoea3. However, its potential as a diagnostic matrix could go well beyond skin-related ailments. We have recently shown that sebum has a critical diagnostic role in other diseases such as Parkinson’s, tuberculosis and COVID-194. Sebum is readily available and an ideal candidate for use in non-invasive diagnostics. In recent work, we have demonstrated that the composition of sebum changes at the onset of a disease. To date, it is typically collected by a cotton swab or similar which is rubbed against the skin to collect the secretions present, with this then sent to a lab for LC-MS analysis. While this works, the rate of sebum creation is highly variable between different people, and normalizing sebum metabolome to sebum production is essential for developing quantitative biochemical assays. There is no standard method now to perform this normalisation. However, developing an analytical assay for normalisation of sebum production per person that is accurate, robust, and cheap will lead to fundamental research in sebum. Certain conditions such as seborrheic dermatitis, age or hormonal changes may change sebum excretion rates, which may change how metabolites are expressed on the skin. Thus, an accessible method to monitor sebum over an extended period with minimal invasiveness could prove ideal for collecting data on this fundamental measurement.
We have been working for several years to create manufacturing approaches to bridge the wearables and flexible electronics areas, creating printed RFID and sensing electronics based wearable devices that are directly compatible with established routes to scaled-up manufacturing5. This includes flexible printed batteries and paper substrates for biodegradability. This project will create next generation manufacturing platform to realize devices with functionality far beyond those currently available and improve the capacity of current printed flexible and stretchable batteries. The project will introduce sebum collection that has never been demonstrated on smart sensor patches and will act as a showcase for the beyond-state-of-the-art sensing using wearable sensors.
A candidate's attributes should include:
• At least a 2:1 or higher degree in electronics, chemistry or related discipline.
• Good communication and presentation skills.
• Previous laboratory experience using related techniques.
• Understanding of the importance of statistical analysis for big, complex
• Desired experience using statistical software and familiarity with -omics
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).