This is a funded MbyRes, including a generous stipend and tuition fees, with well-resourced circumstances for a successful scholarship.
Here is an exciting opportunity to carry out research and development in biomedical electronics which could lead to entirely new approaches in molecular diagnostics.
The selected candidate will apply their programming and embedded systems skills and ambition to design and release a real application product that would make molecular diagnostics faster and more affordable . This project will allow the student to develop transferable knowledge and skills in this most exciting and active field of biotechnology.
This Knowledge Economy Skills Scholarship (KESS) project will be held in the Faculty of Computing, Engineering and Science at the University of South Wales. KESS is a programme funded by the European Social Fund (ESF) awarded by the Welsh European Funding Office (WEFO) in the Welsh Government.
The project is backed by Llusern Scientific Ltd, a Welsh biotech new start-up, that has developed a molecular testing platform technology that is based on the “Loop mediated isothermal amplification” (LAMP) of nucleic acids, with the aim of making molecular diagnostic rapid and affordable worldwide.
Programme of research:
To carry out the day to day tasks of this project. An MbyRes student with background in embedded electronic systems design will be recruited after an open competitive process. The direct supervision of the student will be carried out by Dr Ali Roula who has expertise in signal processing and embedded systems design. Dr Nieuwland will assist with requirement specification and supplying LAMP samples for experimentation and validation. The work in the project will be subdivided into 4 phases of 3 months each:
Phase 1: Background research and requirement specification: During this phase, the student will undertake the required literature survey on LAMP detection and its challenges and limitations. The student will also work closely with LLusern Scientific to understand the operation of the existing LAMP system and in particular, develop an intimate understanding of the firmware code.
Phase 2: Firmware redesign for programmableLAMP: The student will use the existing code version for LodeStar Dx to first design a more sophisticated heating control algorithm to replace the existing simple differential fix temperature control algorithm. This will require investigating various control system approaches including PID control and Fuzzy Logic Control technique. Then the next step would be to investigate and design suitable digital signal processing pre-processing algorithm for photo-detection to ensure optimal signal to noise ratio and maximum dynamic range and signal sensitivity for a range of LAMP reactions.
Phase 3: Data collection and validation: After the firmware has been modified to show that the proof-of concept updated machine can operate reliably for variable temperature ranges and reaction times, the next step would be to test and fine-tune the performance on a selected number of reagents targets, namely 1- Urinary Track Infections (UTI), 2- Respiratory Syncitial Virus (RSV) and 3- EColi. Once variable reaction profiles could be generated, statistically significant learning data set can then be produced with both positive and negative reactions. With such training data available, the student’s last task will be to develop a detection algorithm using machine learning techniques to minimise false negatives. Various approaches will be investigated including Quadratic Discriminant Function, Support Vector Machines (SVM) and Machine Learning approaches such as Artificial Neural Networks or Deep belief Networks.
Phase 4: Thesis Write-up and output publication: As a consolidation of the outcomes of the project and if time allows, the student will work to fully characterise the system and gauge the trade-off between sensitivity vs specificity, the algorithm parameters will be varied and fine-tuned, to obtain ROC curves and compare the new system performance to conventional (slow) gold standards PCR. Findings from the project will be disseminated to suitable journals such as IEEE Transaction in Biomedical Engineering. Sufficient time will be allocated exclusively for the final thesis will be written up viva preparation.
Studentship: The studentship will cover the fees for a full-time MbyRes programme and pay a stipend of circa £11.8k p.a. There is also around £3k project support costs available for consumables, travel, minor equipment, training (including the KESS Grad School) and conference attendance.
To be eligible to hold a KESS studentship, you must:
- have a home address in East Wales area (details below)* at the time of registration.
- have the right to take up paid work in the East Wales area* on completion of the scholarship.
- be classified by the University as ‘home’ or ‘EU’ for tuition fees purposes according to the University’s guidelines.
- satisfy University of South Wales’s admissions criteria: see below, qualifications and experience and application process
- *East Wales area covers: Vale of Glamorgan / Cardiff/ Newport/ Monmouthshire/ Powys/ Wrexham/ Flintshire
Qualifications and experience:
Eligibility of Student:
- Have a degree (2i or higher) in Electronics Engineering or related field
- Possess a reasonable understanding of Embedded systems and design with RTOS
- Be highly self-motivated, with capacity to learn and develop new skills and techniques
- Have well-developed and positively collaborative interpersonal skills
- Have an ability to deliver technical reports and communicate findings
- Be willing to travel and work in industrial / clinical / community support settings
To download an application package, please visit: Participant Application Package
For any queries on eligibility, please contact: KESS Team at Research and Innovation Services, University of South Wales: [Email Address Removed] Tel: 01443 482578
For informal enquiries or further programme information, please contact: Dr Ali Roula ([Email Address Removed]).
Dr Roula staff page can be found here: https://pure.southwales.ac.uk/en/persons/ali-roula(5003f2a1-4896-4616-aa7b-24cba289fbe0).html
Closing date for applications: midnight Monday the 29th of August 2022