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Predicting therapy responses in psoriasis


Faculty of Medicine and Health

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Dr M Wittmann No more applications being accepted Funded PhD Project (European/UK Students Only)

About the Project

Treatment options for inflammatory skin diseases such as psoriasis have greatly improved over the last decade. However, our current inability to predict who will respond best to which treatment causes frustration for both clinicians and patients.

In this project we aim to predict treatment responses by integrating clinical information, serum markers and biological information from the affected organ, the skin. We have previously optimised a non-invasive tape stripping sampling procedure and are able to reliably quantitate several thousand proteins directly from the skin to input in to our “treatment prediction algorithm”. The key challenge is to find “patterns” within these large multiparameter datasets which accurately predict responses to therapy for individual patients. For this we will adapt a machine learning approach (i.e. deep Learning methods, such as convolutional neural network (CNN) and recurrent neural network (RNN)). All different types of data obtained will be used  to design and implement  the pipeline to detect patterns related to clinical outcome.

Training, Supervision and Environment:
The multidisciplinary supervisor team covering clinical dermatology, laboratory-based skin inflammation research and machine learning/AI will ensure a broad development opportunity from clinic, to lab and data analysis. You will join the Leeds PhD training programme. 

Specific training opportunities include
This multidisciplinary studentship will provide extensive experience in machine learning, HPC and cloud computing, bioinformatics, proteomics, skin inflammation, molecular and cellular aspects of psoriatic disease as well as clinical trials methodology.

Eligibility
Candidates are expected to hold (or be about to obtain) a first degree equivalent to at least a UK upper second class honours degree in a related area, which can include biomedical sciences, medical subjects, biochemistry, computer science, data science or bioinformatics. Candidates with interest in proteomics and inflammatory skin diseases are encouraged to apply. Working experience in machine learning, Python programming or Tensorflow, Keras, Pytorch, GPU systems would be most welcome.

The minimum requirements for candidates whose first language is not English are:

• British Council IELTS - score of 6.5 overall, with no element less than 6.0
• TOEFL iBT - overall score of 92 with the listening and reading element no less than 21, writing element no less than 22 and the speaking element no less than 23.

How to apply
To apply for this project applicants should complete a Faculty Scholarship Application form using the link below https://medicinehealth.leeds.ac.uk/downloads/download/129/faculty_graduate_school_-_application_form) and send this alongside a full academic CV, degree certificates and transcripts (or marks so far if still studying) to the Faculty Graduate School at [Email Address Removed]

We also require 2 academic references to support your application. Please ask your referees to send these references on your behalf, directly to [Email Address Removed] by no later than Friday 5 June 2020.

If you have already applied for other projects using the Faculty Application Form this academic session you do not need to complete this form again. Instead you should email the Graduate School to inform us you would like to be considered for this project.

Funding Notes

This PhD scholarship is available for UK and EU citizens only. The scholarship will attract an annual tax-free stipend of £15,285, subject to satisfactory progress and will cover the UK/EU tuition fees. This scholarship project is funded by the Psoriasis Association. 
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