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Adaptive and Predictive Computational Modelling of Biomaterials: A Digital Twin Approach Towards Next Generation Personalised Healthcare (SAM30)

  • Full or part time
  • Application Deadline
    Tuesday, January 14, 2020
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Loughborough University is a top-ten rated university in England for research intensity (REF2014). In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.

Find out more: http://www.lboro.ac.uk/study/postgraduate/supporting-you/research/

Project detail

Healthcare industry is rapidly embracing digital technologies to delivery data-driven personalised medicine. Digital twins are computer-based, or in-silico, models that are replica of the physical object or services. It provides realistic environment to study disease, new drugs and devices without being in close proximity and helps to accelerate life-saving innovations, at reduced cost.

Building upon existing success of the group, the project aims to bridge the current multi-scale finite-element models with advanced medical imaging technique and to create a new paradigm in computational healthcare. The candidate will focus on implementing and validating existing multi-scale models against state-of-the-art high-resolution, in-vivo tissue imaging data collected from leading bio-imaging centre. The collaborative and multi-disciplinary nature of the project will ensure the candidate receives state-of-the-art training, chances to work with leading experts (from industrial and scientific fields) and a multi-disciplinary career paths.

Prior experience in advanced modelling and bio-imaging is not necessary. However, applicants should be able to demonstrate competence and an interest in relevant fields.

Start date of studentship: 01 October 2020.

Entry requirements

Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in engineering, physics, applied mathematics or a related subject. A relevant Master’s degree and/or experience in one or more of the following will be an advantage:

- Mechanical engineering
- Biomechanical engineering
- Solid mechanics
- Applied mathematics
- Physics

How to apply

All applications should be made online at http://www.lboro.ac.uk/study/apply/research/. Under programme name, select ‘Mechanical, Electrical & Manufacturing Engineering’.

Please quote reference number: SAM30

Funding Notes

Applicants who apply for this project will be considered on a competitive basis in March 2020 against candidates shortlisted for this and other projects with the advert reference beginning ‘SAM’. Early submission is advised, and a complete application must be received before the advert’s closing date.

If successful, candidates will be awarded a 3-year school studentship providing a tax-free stipend and tuition fees at the UK/EU rate (currently £15,009 and £4,327, respectively, in 2019-20 which are likely to rise by 2020/21). Non-EU-nationals may apply but the studentship will cover the cost of the international tuition fee only.

Successful candidates will be notified by 26 March 2020.

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