Partnerships Office

Current ICase PhD Student Vacancies

UNIVERSITY OF SALFORD - CURRENT SPONSORED PHD/MSc By Research STUDENTSHIP VACANCIES

Industrial Masters by Research Title: Study to evaluate effectiveness of a Levitex pillow on sufferers of neck pain and impact on the rehabilitation process.

The studentship is with University of Salford and Levitex Foams Ltd.

Academic Supervisor: Jo-Anne Webb (Directorate of Occupational Therapy)

Academic Co-Supervisor: Michael Dean (Directorate of Physiotherapy and Sport)

Industrial Supervisor: James Leinhardt

The studentship is fully funded and includes:

  • A fee waiver
  • A stipend of £15,824
  • All bench fees and consumable costs
  • Funds specifically allocated for conference travel

Final date for applications: 15.7.19

Interviews will be held on: Week beginning 29.7.19

The candidate must be in a position to register by September 2019

Description:

Levitex foams Ltd has designed and patented a brand-new polyurethane foam technology. Following a successful independent clinical comparative study of mattresses at The University of Salford this year, along with 20 case studies of patients with varying degrees of neck pain there is an identified needto further evidence the clinical benefits of a Levitex foam pillow as an intervention for patients with neck conditions.

A good pillow should hold the head in the correct alignment, that is in the same relation to the shoulders and spine as if standing upright with the correct posture – and be tucked well into the neck and shoulder to support the head fully. The nature of Levitex foam is such that the user doesnot need to apply a large force for it to compress to 65% of its original size, providing the softness and moulded feel one would get from a high quality memory foam pillow. However, a much greater force is required to compress the pillow to 25% of its original size, offering firmness one might find from a conventional foam or high resistance foam. By combining these two features, case studies suggest that the foam can support the “clinical” requirements of a good pillow.

From the perspective of healthcare, too little emphasis is placed on posture and the long-term effects of a continuous battle against gravity. Furthermore, there is very little research into the relationship between what we lie on and proprioception. The average time it takes a new intervention to be realized in healthcare is currently sixteen years. Independent clinical evidence will accelerate this process to enable Levitex foam pillows to be available alongside current treatments as an intervention for neck pain.

The aim of this project is to create a study to evidence the benefits of Levitex foam pillows in improving patient outcomes for those patients suffering with a variety of neck pain. The minimum requirement being that they have suffered at least two weeks of continuous neck pain. The study will evaluate the impact of the Levitex pillow as an intervention following neck pain, evaluating levels of pain and impact on activities of daily living.

Candidates: Applicants will be expected to hold an upper second-class honours degree or better in Occupational Therapy, Physiotherapy or any Health Care Profession and have an interest and / or clinical experience in postural management or musculoskeletal injury. They should demonstrate excellent communication skills through a variety of modes of communications, with a diverse range of individuals and have excellent self-management skills. Data analysis and management skills are desirable with and some prior experience of writing a research proposal advantageous.  

As part of your application, please provide a CV, covering letter and outline research proposal. The proposal should include a brief literature review related to this project, with an outline of the methodology you would propose to answer the aims of the Masters. The proposal should be no more than5 pages, single line spaced, 12-point font, Times New Roman.

For full details of student requirements and specification please visit: http://www.salford.ac.uk/ktp/industrial-case-studentships/vacancies

Funding Eligibility:

Students must be able to demonstrate a relevant UK connection whether this be a UK/EU National or an ordinarily resident for a period of 3 years immediately prior to the date of application for an award.  

Enquiries: Informal enquiries should be made to Jo-Anne Webb or Mike Dean by email:

j.webb@salford.ac.uk

M.Dean@salford.ac.uk

Curriculum vitae, research proposal and cover letter (supporting statement) explaining their interest should be sent to v.l.beckett@salford.ac.uk


PhD Title: Blast noise prediction and management

The studentship is with University of Salford and Spadeadam Testing & Research Centre (STaR)

Academic Supervisor: Professor David Waddington

Academic Co-Supervisor: Dr Sabine von Hunerbein

Industrial Supervisor: Paul Cronin

The studentship is fully funded and includes:

  • Full fee waiver  
  • Enhanced stipend of £16444 p.a. for 3½ years, plus paid accommodation at Spadeadam for years 2 and 3  
  • Bench fees and consumable costs  
  • Funds specifically allocated for conference travel  

Final date for applications: 30th June 2019  

Interviews will be held on: July/Aug 2019

The candidate must register by 1st September 2019

Description

We are looking for a PhD candidate to work on developing methods for explosive noise impact prediction and management. The successful candidate will be expected to undertake experimental trials, model long-range noise propagation, and develop procedures to manage adverse human impact in the near and  farfield. The candidate will spend 1 year at the University of Salford followed by 2 years at STaR.

Background

Part of the DNV GL Group, the Spadeadam Testing and Research Centre (STaR) conducts a wide variety of fire, explosion and blast testing for the maritime, oil & gas, power and renewables  industries.DNV GL’s strategic aim is to make its STaR a world-leading test facility, and to achieve this it is necessary to ensure that the business is not put at risk from adverse reactions to noise in the surrounding areas. Improved noise prediction should allow:

  • Improved scheduling of trials, reducing costs from potential delays.  
  • Larger explosion trials to be conducted without generating noise disruption.  
  • Extension of the season, increasing the number of trial slots.  

The STaR test facility in the North of England is an area of complex meteorology and topography for which existing models are unreliable. This means that the system to make blast noise predictions for the STaR site will need to be the first of its kind in the world.

STaR is likewise interested in researching new ways to reduce risk to hearing from short duration, high-level explosive noise to allow them to best protect their employees, visitors and clients. This will allow STaR to confidently maximise the number of test opportunities while minimising noise risks to hearing.

Candidates

We are looking for high quality candidates with an expertise in the following areas;

  • Cognate acoustics, mathematical, physics, engineering, meteorology or computer sciences background
  • Good computer programming skills
  • Experience of experimental measurement, preferable environmental noise
  • Highly numerate with experience of data analysis
  • Ability to work independently and within teams
  • Strong written and verbal communication skills

Funding Eligibility

To be eligible for the full maintenance grant, students must be a UK/EU National or be able to demonstrate a relevant connection with the UK, usually through being ordinarily resident for a period of 3 years immediately prior to the date of application for an award. Member states of NATO will also be considered

Enquiries: 

Informal enquiries to Professor David Waddington: d.c.waddington@salford.ac.uk

CV and supporting statement to m.watts@salford.ac.uk

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PhD in Biomedical Engineering: Development of a neuro-prosthesis for hand-arm rehabilitation after stroke

The studentship is with University of Salford and Shandong BetR Medical Technology Co. Ltd.

The studentship is fully funded and includes:

  • A fee waiver  
  • A stipend of  £15,824 p.a. for three and a half years
  • All bench fees and consumable costs  
  • Funds specifically allocated for conference travel  

Final date for applications: 30th June 2019  

Interviews in July 2019

The candidate must register by 1st September 2019

Description

After a stroke many people cannot use their affected arm because of partial paralysis and this has considerable impact on their quality of life. Intensive physiotherapy can help people to regain use of their arm, but a major problem is the limited availability of physiotherapists, who act as clinically qualified personal trainers. Therefore, home-based rehabilitation systems that do not require the presence of a physiotherapist are needed to give the best chance of recovery through relearning and brain plasticity.

Functional Electrical Stimulation (FES) of muscles is a high-tech but potentially low-cost solution, which directly activates paralysed muscles through electrical stimulation via skin-surface electrodes. In contrast to traditional physiotherapy, FES provides a means of directly tapping into the nervous system, actively producing muscle contraction and movement, exciting many of the associated neural pathways. If this is synchronised with the patient’s efforts to carry out meaningful tasks, it provides sensory neural inputs associated with the intention to create functional movement, which isideal for promoting relearning  and brain plasticity.

However, current FES systems for hand-arm therapy rely on the presence of a specialist physiotherapist who understands how to adjust the stimulation applied to relevant muscles to help the patient undertake training exercises. This is more difficult than it sounds because the patient will have some ability to voluntarily contract their muscles and the FES must provide enough support but not too much, so that the patient is continually challenged whilst achieving the training exercises. So, automating this is a more difficult problem than simply controlling the movement of the patient's arm in the same way that a robot arm would be controlled.

The system we envisage would sense arm movement but, rather than using traditional trajectory following feedback control (e.g. robot control), it will need to estimate the level of voluntary effort achieved by the patient and adapt muscle stimulation to compensate for their improving performance or fatigue to keep the training exercises challenging but achievable. At present FES control parameters are adjusted manually, by trial and error, and it is unclear how this can be formalised so that it can be automated. To solve this problem you will:

  1. Use a heuristic rule-based system informed by knowledge elicitation from a group of FES specialists.
  2. Use machine-learning methods that can automatically learn from FES specialists.
  3. Apply the algorithms developed in i) and ii) in an iterative learning manner to track the patient's changing voluntary effort.

Working closely with our industrial partner, Shandong BetR Medical, and also our team of research physiotherapists, you will produce and test a prototype neuro-prosthesis based on your new learning algorithms. Therefore, you will have the opportunity to work for short periods at the company, which is based in Jinan City, China. Shandong BetR Medical is a small spin out company led by Dr Mingxu Sun who was a researcher in our team at Salford up until 2018.      

Your PhD will build upon our previous work on FES, for example follow these links: https://www.frontiersin.org/articles/10.3389/fneur.2019.00227/fullhttps://www.frontiersin.org/articles/10.3389/fnins.2018.00449/full

You will join a vibrant research group, which currently holds around £8 million in research funding from EPSRC, NIHR and charities, including hosting the UK’s Centre for Doctoral Training in Prosthetics and Orthotics. For more information, see https://www.salford.ac.uk/research/health-sciences/research-groups/human-movement-technologies

For the latest news on our group, see https://twitter.com/UoSRehabTech

Candidates

This PhD will suit candidates with a strong interest in Biomedical Engineering, including prototyping and testing (with patients) of solutions that include sensing, stimulation hardware, and embedded software. Candidates should have a first or upper second-class honours degree in an area relevant to the proposed research. This includes engineering, physics, mathematics or computer science. Candidates with other closely related first degrees should contact Prof Howard to discuss their eligibility.

For full details of student requirements and specification please visit: http://www.salford.ac.uk/ktp/industrial-case-studentships/vacancies

Informal enquiries may be made to Prof David Howard by email: d.howard@salford.ac.uk

A curriculum vitae and supporting statement, explaining your motivation and interests, should be sent to both V.L.Beckett@salford.ac.uk and d.howard@salford.ac.uk

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PhD Title: Transferability of plant pest models

The studentship is supported by the University of Salford and Defra

Academic Supervisor: Dr Stephen Parnell

Academic Co-Supervisor: Dr Katherine Yates

Industrial Supervisor: Sam Grant

The studentship is fully funded and includes:

  • A fee waiver  
  • A stipend of £15,824 p.a. for three and a half years
  • All bench fees and consumable costs  
  • Funds specifically allocated for conference travel  

Final date for applications: 30th June 2019  

Interviews will be held on: 17th July 2019

The candidate should be able to register by a preferred start date of 23rd September 2019

Description

Applications are invited for a research project in collaboration with the Department for environment, food and rural affairs (Defra) to investigate the use of data and modelling to enhance the UKs response to the growing tide of invasive plant pests and diseases.  

There has been a substantial rise in invading plant pests and disease in recent times with changes in climate and global trade and travel. Recent examples include ash dieback and the emerald ash borer, which threaten Ash in the UK, and Xylella fastidiosa which is currently devastating olive crops in Italy and is a threat to multiple host species in the whole EU region. Disease distribution and spread models are commonly used to map the risk of potential invaders in new areas (1).  This relies on parameterising and validating models using data in areas where a pest already exists, and then transferring predictions to areas where the pest does not occur (2).  This project will address the extent of this transferability, which has significant implications for pest risk assessment and effective targeting of surveillance programs.

The student will develop skills in spatial analysis, distribution modelling and R, as well as having the chance to be involved in multiple international collaborations. Candidates should have a degree in Biology, Ecology, Environmental Science, or similar, with strong quantitative skills. The studen will spend part of their time working within Defra (based in Defra offices in London, Bristol or York depending on project needs). Candidates with degrees in quantitative subjects (maths, physics etc) and a demonstrable interest in environmental applications will also be considered.

1. Parnell, S., van den Bosch F.,Gottwald, T.R. and Gilligan C.A. 2017. Surveillance for emerging plant disease; an epidemiological perspective. Annual Review of Phytopathology. https://doi.org/10.1146/annurev-phyto-080516-035334

2. Yates, K., Bouchet,P., Caley, J., Mengersen, K., Randin, C.F., Parnell, S. et al. 2018. Outstanding Challenges in the Transferability of Ecological Models. Trends in Ecology and Evolution. https://doi.org/10.1016/j.tree.2018.08.001.

Candidates

Applications are invited for a fully-funded PhD studentship partnered with the Department for environment food and rural affairs (Defra) exploring the transferability of epidemiological models for improved plant biosecurity.

Funding Eligibility

This studentship is only available to students with settled status in the UK, as classified by EPSRC eligibility.  Please visit: https://www.epsrc.ac.uk/skills/students/help/eligibility/

Enquiries: Informal enquiries may be made to Dr Stephen Parnell by email: S.R.Parnell@salford.ac.uk

Curriculum vitae and supporting statement explaining their interest should be sent to V.L.Beckett@salford.ac.uk