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Context-Aware Data-Driven Approach to Enhance the Wellbeing of Workers in Complex Scenarios (SAM28)


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

This project will investigate an objective and reliable data-driven approach based on wearable technologies for human workers to support initiatives and actions to improve their wellbeing in complex scenarios (e.g. working with robots, virtual/augmented reality tools). Novel wearable sensing technologies can be used to understand the health and emotional wellbeing (e.g. exposure to stress, increased mental workload), through understanding of multimodal biometric data and advanced data analytics and machine learning, to accurately detect changes in health, emotion and mental workloads.

One of the challenges to realise such tools in real-life settings, and the key novel contribution in this project, is in the incorporation of context-awareness to improve the reliability of data-driven approach through use of multi-modal sensor fusion or development of a priori knowledge model. A potential focus could be on the aging workforce and how their wellbeing can be supported and augmented, especially in comparison with the younger workforce. The PhD will be working across multidisciplinary research labs and will be able to access to equipment and resources as appropriate.

Find out more: https://www.lboro.ac.uk/departments/meme/research/systems/

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 robotics, mechatronics, biomedical engineering, or a related subject. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: computer science, human-robot interaction, robotics, AI and machine learning.

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: SAM28

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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