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POSITION NOW CLOSED PhD Title: Developing and evaluating a force plate testing battery for monitoring lower body neuromuscular function

UNIVERSITY OF SALFORD

 

PhD Title:  Developing and evaluating a force plate testing battery for monitoring lower body neuromuscular function

The studentship is with University of Salford and Hawkin Dynamics, Inc.

 

Academic Supervisor: Dr John McMahon

Academic Co-Supervisor: Dr Paul Comfort

Industrial Supervisor: Dr Peter Mundy

The studentship is fully funded and includes:

 

  • A fee waiver for tuition fees
  • A stipend of £16,298 p.a. for three and a half years
  • All bench fees and consumable costs
  • Funds specifically allocated for continued professional development, including conference attendance and travel

Final date for applications: 21st April 2021

Outcome of application to be sent out: 28th April 2021 

Interviews will be held virtually on: 4th May 2021

The candidate must be in a position to register at the University by 17th May 2021

Description:

Force plates are now among the most frequently used biomechanical apparatus in the field of strength and conditioning (S&C). The rise in use of force plates among S&C coaches is likely due to the advent of affordable and valid portable force plates that have been developed and released commercially. Some limitations of these recently developed force plates, despite their affordability, include that they are wired systems (meaning that they require an external electrical supply which restricts testing locations) and they either do not come with test analysis software, or the included software does not automate calculations or, in some cases, the software does not include recommended calculations for a broad range of tests, thereby limiting the utility of the resulting data. Thus, despite force plates now being commonplace in the S&C domain, with many S&C coaches testing their athletes daily, how to best utilise force plates to inform decision making in sport is yet to be fully realised.  

The World’s first wireless dual force plate system was recently developed by Hawkin Dynamics (HD) and it has since been purchased by many S&C practitioners who work with elite athletes around the World. As well as producing robust and fully portable force plates, HD have also developed proprietary software which automatically calculates a range of variables across several tests and reports data immediately after the test has been conducted. Thus, athletes can be tested using robust procedures within a few minutes and coaches can gain immediate access to their athletes’ scores. Therefore, the HD hardware and software has the potential to revolutionise the way in which force plate assessments are conducted globally. However, there is a lack of research on how best to integrate multiple force plate tests (e.g., dynamic assessments and isometric assessments), when conducted using appropriate methods, to provide a comprehensive evaluation of athletes’ lower body neuromuscular function. Consequently, rigorous research is required to develop and evaluate sports-specific force plate testing batteries for monitoring lower body neuromuscular function. This would allow for research-informed force plate testing batteries for monitoring both acute and chronic changes in athletes’ lower body neuromuscular function to be embedded into the HD force plate software and subsequently applied by practitioners globally.

Aims and Objectives

The overarching aim of the proposed work is to develop and evaluate a force plate testing battery for monitoring lower body neuromuscular function across multiple sports. This will be achieved by four main studies that address either the development or the evaluation aspects of the research. The specific objectives of the research are:

•             To develop a meaningful force plate testing battery for assessing lower body neuromuscular function

•             To facilitate automatic interpretation of force plate data across the testing battery

•             To help inform practitioner decision making regarding athlete training requirements

 

Eligibility

We are seeking applications from highly motivated candidates who have an exceptional understanding of force plate analyses. Applicants should have previous experience of conducting force plate testing batteries with athletes and be able to demonstrate their ability to effectively communicate key results of force plate tests to diverse audiences, including athletes, coaches and sports scientists. Applicants should also have excellent computer processing skills and strong understanding of data analytics.

Applicants will be required to travel to the USA to work with the HD team for a minimum duration of three-months, spread across the PhD project. Thus, applicants must hold a valid passport and be permitted to travel to the USA when required.

Applicants should hold a minimum of an upper second class (2:1) honours degree (or its equivalent) in Sport and Exercise Sciences or Strength and Conditioning. We strongly encourage candidates who have a Master's degree in Sport and Exercise Sciences (or Strength and Conditioning or Sports Biomechanics) to apply. We also particularly encourage applications from individuals who represent groups who are traditionally underrepresented in strength and conditioning and applied sports science.

We would normally expect the academic and English Language requirements (IELTS 6.0 overall with 5.5+ in each component) to be met by point of application. Details of the University’s English Language entry requirements can be read here: https://www.salford.ac.uk/international/english-language-requirements#:~:text=AS%20Level%20English%20(all%20UK%20boards)%3A%20Grade%20D.&text=TOEFL%20IBT%20and%20TOELF%20IBT,%2D%2017%3B%20speaking%20%2D%2020.&text=Pearsons%3A%2060%20%3D%206.5%20IELTS%2C,IELTS%2C%2051%20%3D%205.5%20IELTS.

Applicants will be shortlisted for interview based on the information above and the quality of the 5-page (maximum) research proposal detailing how they would approach the topic, based on the aims above.

Funding Eligibility: 

This studentship is only available to students with settled status in the UK, or any European Union country.

 

Enquiries: Informal enquiries may be made to Dr John McMahon by email: j.j.mcmahon@salford.ac.uk

Applicants should send their curriculum vitae, a supporting statement explaining their interest in the PhD project and a 5-page (maximum) research proposal detailing how they would approach the topic, based on the aims above, to m.watts@salford.ac.uk by the application deadline.

Applicants who are invited to the interview stage of the recruitment process should expect to prepare a short presentation for the interview. Details of the presentation will be provided as part of the interview invitation.

POSITION NOW CLOSED PhD Title:  Deep Active Learning for Detecting Asset Degradation

PhD Title:  Deep Active Learning for Detecting Asset Degradation

The studentship is with University of Salford and Add Latent Ltd.

 

Academic Supervisor: Dr Julian Bass

Academic Co-Supervisor: Dr Tarek Gaber

Industrial Supervisor: Hossein Ghavimi

The studentship is fully funded and includes:

  • An MPhil/PhD fee waiver
  • A starting stipend of £18,000 p.a. for three and a half years
  • All bench fees and consumable costs
  • Funds specifically allocated for conference travel

Final date for applications: 31/05/2021

Interviews will be held on: 15/6/2021

The candidate must be in a position to register by 27/9/2021

Description:

The aim of this research project is to use video data and the latest machine learning techniques to detect component deterioration in Internet of Things applications. We are excited by the opportunities presented by the latest Deep Active Learning approaches which you will have a chance to enhance and apply in this research. On the one hand, active learning (AL) maximizes a AI model’s performance gain using as few samples as possible. On the other hand, deep learning requires large quantities of training data to extract high-quality features. Deep active learning techniques are exciting because they seek to combine the strengths of both approaches. The Internet of Things and Industry 4.0 are exciting application areas for AI researchers, with considerable growth in recent years.

While you will have a chance to develop your own research plan, we envisage these aims will be achieved through three main phases of work. First, establishing a laboratory-based experimental apparatus for testing and evaluating approaches to video detection of asset degradation. Second, creating novel approaches to video detection of asset degradation. Thirdly, using video data to overlay identification information derived from databases.

This is a great opportunity to join an award-winning research team and to work on a cutting-edge research project applying AI in an Internet of Things application. The successful candidate will become a thought leader in artificial intelligence and have the opportunity to work with potential clients and company subject matter experts.

Computer Science at Salford is ranked in the top 400 departments world-wide (Times Higher Education, World University Ranking, 2021) and Julian Bass was University of Salford, Research Supervisor of the year in 2020 and is Head of the Informatics Research Group.

Add Latent Ltd. and the University of Salford have been collaborating for over five years. This includes two award winning Knowledge Transfer Partnership (KTP) projects which both received top-scoring certificates of excellence from Innovate UK. Add Energy were also recently awarded the Queens Award for Enterprise in International Trade due to their fast pace of growth.

Add Latent Ltd. have already created an R&D capability using an agile software development process and have an impressive client list of major companies in the industrial marine and energy sectors. Their expertise in maintenance optimisation gives them unique access to large industrial plants.

Candidates:

The successful candidate will join the Informatics Research Group at University of Salford and develop expertise machine learning and video processing. In addition, the Add Latent team will be on-hand to advise about asset integrity,

You will hold (or expect to obtain) a Masters degree or minimum of an upper second class honours degree in an area of computer science, software engineering or a closely related discipline. Experience of working in the commercial digital technology sector would be an advantage.

As part of your application please provide a CV and covering letter.

Funding Eligibility:

This studentship is only available to students with settled status in the UK.

Enquiries: Informal enquiries may be made to Julian Bass by email: j.bass@salford.ac.uk

Curriculum vitae and supporting statement explaining their interest should be sent to m.watts@salford.ac.uk