In-silico analysis of tissue specificity of dermal exposure, deposition and absorption kinetics
This PhD project aims to develop a mechanistic model for in-silico analysis of tissue specificity for dermal deposition, penetration and absorption due to either unwanted exposure to environmental pollutants or intended topical administration of skin care products.
It will cover the tuition fee at UK/EU level, and provide a PhD stipend (c. £18,000 per annum), as well as generous budget for training.
Human skin is a complex organ of human body with multi-layer tissues and multiple components such as sweat ducts and glands, sebaceous glands and hair follicles. Understanding the tissue specificity of dermal exposure, deposition and absorption underpins a range of important areas in transdermal drug delivery, cosmetic care, safety assurance and protection from pollution. Targeted topical delivery to specific skin tissues plays important roles in human health, e.g. skin ageing, inflammation, allergy, and as route for drug delivery. There has been an increasing research in the overall dermatopharmacokinetics of percutaneous absorption in recent years, but there is very limited understanding on how dermal exposure leads to the uptake by specific tissues. Existing computer models are mostly limited to one-dimension without considering the complex skin tissue specificity.
This work will be based on the latest advancements in multi-scale modelling of transdermal bioavailability at the University of Surrey, in collaboration with Unilever. The existing model will be extended to include complex skin tissues of sweat and sebaceous ducts. Furthermore, computational fluid dynamics will be applied to model microscopic shearing and spreading on complex skin contour under typical dermal exposure conditions. Discrete element method will be used to predict tissue specific dermal deposition of soluble solids, volatiles and particulate matter from either air or skin care vehicles. Published experimental data will be reviewed, analysed and used for model validation. The PhD student will be jointly trained by the University of Surrey and Unilever, with substantial exposure to both fundamental research and industrial research and development.
Applicants should have:
- A minimum of a 2:1 UK honours degree (or equivalent) in either engineering, physics or chemistry
- Experience in computer programming and/or mathematical modelling
- A masters degree is not a pre-requisite but would be looked upon favourably
- Non-native speakers of English who did not study in an English-speaking country will be required to have IELTS 6.5 or above.
How to apply
Formal applications can be made through our Chemical and Process Engineering Research PhD course page.
Applications will be reviewed when received, and shortlisted candidates will be interviewed. The position will remain open until a suitable candidate is found.
The application shall include:
- A cover letter (maximum of one page) explaining your interest and suitability for the project
- A curriculum vitae (maximum of two pages)
- Published work such as journals and conference articles
- A copy of your academic transcripts
- A copy of your postgraduate taught dissertation (if appropriate)
- Names and contact information of at least two referees
- If applicable, a copy of a valid IELTS certificate from the past two years.
Application deadline: Applications accepted all year round