PhD Studentship, Clinical and Experimental Sciences

Southampton, United Kingdom
01 Jun 2021
End of advertisement period
15 Jun 2021
Contract Type
Fixed Term
Full Time

Clinical and Experimental Sciences

Location:  Southampton General Hospital
Closing Date:  Tuesday 15 June 2021
Reference:  1369721FC

Microbial immunity in the skin: Mathematical modelling of host microbiome interactions to elucidate the contribution of yeast microbes in regulating skin inflammation

Main Supervisor: Michael Ardern-Jones (Clinical Experimental Sciences)

Other members of the supervisory team: Marta E Polak (Clinical Experimental Sciences) and Fei-Ling Lim (Unilever)

Duration of the award:  Full time 4 years

Amount of stipend and fees:  This project is a Biotechnology and Biological Sciences Research Council (BBSCRC) CASE Studentship. This is a UK fully-funded PhD, with stipend in the range advised by the BBSRC (£15,609.00).   In addition a supplement of £4000 a year is offered by Unilever.

Project overview

Microbial dysbiosis of the skin is associated with a spectrum of very common inflammatory skin conditions including seborrhoeic dermatitis and atopic dermatitis (AD).  Malassezia yeasts have been recognized to play an important role in the regulation of skin inflammation and dysbiosis, but the precise mechanisms of how the yeast may regulate immune responses in skin are not understood. It is likely that as well as interactions with skin, Malassezia also interacts with other members of the skin microbiome.

We have established a machine learning system for analysing RNA transcriptome datasets of in vivo skin inflammation so that we can distinguish microbial interactions with different skin cells.   We have previously showed that S. aureus (SA) colonisation of skin induced a strong IL-17/23 pathway signal whereas S. epidermidis (SE) induced strong upregulation of the negative regulator of inflammation NF-κB inhibitor A20 (TNFAIP3).  In further collaborative work by employing a machine learning approach (Cibersort) we were able to classify skin inflammation from human samples based on IL-17 mediated keratinocyte responses. This mathematical method of data analysis has allowed us to infer specific modifications to the IL-17 signature during progression of inflammation (acute versus chronic) and also in response to anti-inflammatory treatment. 

Here we propose to use our established methodology to investigate the cross-talk between Malassezia and skin inflammation. We will explore whether Malassezia sensing by skin keratinocytes is critical to the maintenance of the healthy bacterial microbiome architecture on skin.

Please contact:   Michael Ardern-Jones.

Person Specification:  See below

Required qualifications:

  • A 1stor 2:1 degree in a relevant discipline and/or second degree with a related Masters

The suited candidate is expected to have either excellent qualifications in biological and chemical sciences (cell biology, immunology, molecular biology, biochemistry, chemistry) and demonstrate ability to learn computational modelling approaches (statistical analysis, coding, machine learning).  

Administrative contact and how to apply:

Please complete the University's online application form, which you can find at

You should enter Dr Michael Ardern-Jones as your proposed supervisor. Informal enquiries relating to the project or candidate suitability should be directed to Dr Michael Ardern-Jones,

Closing date: 15/06/2021

Interview date: 08/07/2021

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