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PhD Studentship - BioMarkML: Machine Learning-Driven Bio-Sensing for Early Diagnosis of Alzheimer’s Disease

University of Plymouth

Qualification Type: PhD
Location: Plymouth
Funding for: UK Students, International Students
Funding amount: £19,088
Hours: Full Time
Placed On: 19th January 2024
Closes: 15th March 2024

DoS: Asiya Khan (asiya.khan@plymouth.ac.uk, tel.: +44 1752 586 123)

2nd Supervisor: Shakil Awan (shakil.awan@plymouth.ac.uk, tel.: +44 780 370 9407)

3rd Supervisor: Amir Aly (amir.aly@plymouth.ac.uk, tel.: +44 1752 586 077)

4th Supervisor: Torsten Bossing (torsten.bossing@plymouth.ac.uk, tel.: +44 1752 437 414)

Applications are invited for a 3.5 year EPSRC funded PhD studentship. The studentship will start on 1st October 2024.

Funding for: UK Students, International Students

Funding amount: The studentship is supported for 3.5 years and includes full Home tuition fees plus a stipend of £19,088 per annum 2024/25 rate (TBC).

Project Description

Alzheimer’s Disease (AD) represents approximately 60% of all dementias and affects over 33 million people globally costing healthcare systems 1% of global GDP to diagnose, treat and care for patients. In the UK over 0.6 million people suffer from AD costing over £16b/y. Therapeutic strategies depend on the diagnosis of AD as early as possible to prevent cognitive deficits before they occur.

In this PhD project we will exploit machine learning (ML) techniques to enable classification of case vs control data sets for protein AD biomarkers using multiplexed graphene sensors that have already been demonstrated to have ultra-high sensitivity and specificity. The ML stage will involve; (i) Feature Selection: pre-processing bio-signals (conductance & impedance) for analysis, employing techniques to iteratively remove the least important features and prevent model overfitting, and utilizing ML models  to assess and rank feature importance; (ii) Pattern Discovery: through clustering approaches to understand the underlying patterns of bio-signals and to inform the classification process; (iii) Classification: to differentiate Alzheimer's patients and healthy controls; (iv) Validation: to rigorously evaluate the classification model's performance and ensure its reliability and generalizability, and (v) Optimisation: tuning hyper-parameters or refining the data pre-processing to optimize the model’s performance.

The pioneering nature of this research will enable integration of ML algorithms with graphene sensors to realise a Point-of-Care (PoC) System. The successful candidate will join a multidisciplinary team spanning AI/ML, biochemistry/biophysics, electronics and clean room-based fabrication of sensors, including access to facilities and expertise from our industrial partner Zimmer & Peacock Ltd.

Eligibility

Applicants from the wide area of artificial intelligence or computer science are encouraged to apply and should have a first or upper second class honours degree (or equivalent from outside the UK) in any of the following subjects; AI/ML, Computer Science, Biochemistry, Electronics or Physics and preferably a relevant Masters qualification. Applications from both UK and overseas students are welcome.

The studentship is supported for 3.5 years and includes full Home tuition fees, Bench fee plus a stipend of £19,088 per annum (2024/25 rate TBC). The studentship will only fully fund those applicants who are eligible for Home fees with relevant qualifications. Applicants normally required to cover International fees will have to cover the difference between the Home and the International tuition fee rates. The international component of the fee may be waived for outstanding international applicants.

If you wish to discuss this project further informally, please contact Dr. Asiya Khan (asiya.khan@plymouth.ac.uk).

To apply for this position please click the Apply’ button.

Please clearly state the name of the studentship you are applying for on the top of your personal statement.

Please see here for a list of supporting documents to upload with your application.

For more information on the admissions process generally, please contact research.degree.admissions@plymouth.ac.uk.

The closing date for applications is 12 noon on 15th March 2024. Shortlisted candidates will be invited for interview shortly thereafter.

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