The link to the position advertisement is  http://jobs.nottingham.ac.uk/ENG1305 .

Applications are invited for an exciting fully-funded PhD studentship in the Bioengineering Research Group, Faculty of Engineering at the University of Nottingham.

Research area. The research topic focuses on developing solutions that enable in-natura markerless motion capture for biomechanical modelling in Biomedical and Sports Engineering. Specifically, it addresses the fundamental research problem of reconstruction of person-specific human pose, kinematics, and surface geometry to enhance our understanding of the non-linear behaviour of human motion, musculoskeletal injury and disease and enable modelling of soft-tissue dynamics. Open problems in human-object interaction and tracking will also be explored.

The project. The candidate is expected to develop a fast and robust method for inferring and tracking 3D shapes of deformable objects, humans in particular. The method will be mainly based on visual sensing. Inertial and force sensors will be used as complementary sensing. The method can use either or both of model-based and learning-based approaches, such as CNN based segmentation, geometric CNNs, or convolutional kernel filter based tracking. The candidate will have access to a newly established state-of-the-art integrated motion capture laboratory.

The candidate. The ideal candidate will have;

1. a first or upper second class honours or Masters degree in Electrical and Electronic Engineering, Physics, Computer Science or other relevant and equivalent degree from a quality recognised institution.
2. a solid background in mathematics and excellent analytical and numerical skills, as well as problem solving skills
3. strong background in 3D computer vision, pose estimation, shape reconstruction, structure from motion, segmentation, or object detection.
4. experience in image or video processing and digital signal processing.
5. strong programming skills in Matlab, C/C++, or Python. Previous hands-on experience with deep learning platforms and agile software development as well as experience of working within industry will be an advantage.
6. very good written and communication skills and fluency in English.
7. a driven, independent professional and self-reliant work attitude within a fast-paced & collaborative environment.

Informal enquiries about the project may be addressed to Dr Ami Drory. Please (i) insert your cover letter, CV and copies of academic transcripts into a single pdf file. (ii) Name the file with your name as ”firstName_lastName_phd”. (iii) e-mail to: Ami.Drory@nottingham.ac.uk, with [3D shape reconstruction PhD application – lastName] as the email subject.

Application instructions. Formal applications are to be made via http://www.nottingham.ac.uk/pgstudy/apply/applyonline.aspx

Closing date for applications. Review of applications will commence on 15 October 2019 and remain open until filled. A start date is expected to be as soon as practical thereafter.

The University. The University of Nottingham is a world-class University consistently ranked among the world’s top 100 universities. It is a Russell Group university and a member of Universitas 21 (U21), the global network of research-intensive universities. The University is ranked eighth in the UK on ‘research power’ in the latest REF rankings. The Faculty of Engineering is ranked in the top 10 in the UK with more than 98 per cent of its research ranked of international quality, with 85 per cent graded as ‘world-leading’ or ‘internationally excellent’.

The university was awarded the University of the Year for both International and Sports in the 2019 Guide. With award-winning campuses, University Park is The University of Nottingham’s largest campus at 300 acres. The campus is widely regarded as one of the largest and most attractive in the UK. Set in extensive greenery and around a lake, University Park campus has consistently won a Green Flag Award for its green and environmentally friendly spaces every year since 2003. The University of Nottingham was ranked the World’s second greenest university in 2019 (GreenMetric). The brand new £40 million David Ross Sports Village is now open, offering an inspirational and accessible sports provision for all.

A stochastic finite-element model for predicting changes in bone strength

Closing date 22/09/2019

Employer: The University of Sheffield (Department of Mechanical Engineering)

Location: Sheffield, UK

Description

Are you a bright, enthusiastic and self-motivated student interested in a PhD in biomechanics? An exciting multidisciplinary PhD opportunity is now available at the Insigneo Institute for in silico Medicine at the University of Sheffield, UK.

Pharmacological interventions that target improvement in bone strength typically seek to improve bone morphology (geometry). Yet, a model to predict change in strength, given knowledge of bone morphology changes, has not received much attention. The recently awarded project MultiSim2 (supported by the EPSRC, UK) will engage with this ageing-related challenge.

Previously in MultiSim, in vivo micro-computed tomography enabled quantification of bone geometry changes in small animals (e.g. mice) with unprecedented spatial and temporal detail. The PhD student will use this information to:

• Capture bone geometry changes driven by cellular processes using Gaussian Process emulators;
• Implement a stochastic finite-element (sFE) model to predict bone strength changes in response to emulator parameters;
• Analyse the global sensitivity and uncertainty propagation of the sFE model.

The expected start date for this project is December 2019.

About the University of Sheffield
The University of Sheffield is a Russell Group university, which represents the 24 leading UK universities committed to maintaining outstanding research and teaching environments. The University of Sheffield regularly ranks among the top 10 in the UK in terms of research output. In addition to having a long tradition of world-class engineering research, Sheffield benefits from geographical proximity to the industrial cities of Manchester, Liverpool and Leeds.

The ambition of the Insigneo Institute is to achieve a transformational impact on healthcare. As such, it possesses extensive experience in the development of computer simulations aimed at better understanding of the biomechanics of the musculoskeletal system. This project will be co-supervised by Dr Pinaki Bhattacharya, Dr Enrico Dall’Ara and Prof Visakan Kadirkamanathan. It will benefit as well from the multidisciplinarity of MultiSim2 research.

Candidate Profile
The successful candidate should have or be expected to obtain an excellent degree in mechanical engineering, bioengineering, computer science, physics, applied mathematics or a related discipline. Experience in finite-element analysis and in programming languages (e.g. C, C++, Matlab, Python) are essential. Exposure to high-performance computing is desirable.

Funding and Duration
A 3.5 year studentship, co-funded by the Departments of Mechanical Engineering, Oncology and Metabolism and Automatic Control and Systems Engineering, is available for UK and EU applicants. The studentship covers the cost of tuition fees and provides an annual tax-free stipend at the standard UK research rate.

How to apply?

To apply please use our standard on-line PhD application form and indicate on your form that you are replying to this advert or email me-pgadmit@sheffield.ac.uk for further guidance on applying.

Contact details

For further information about this project, please contact Dr Pinaki Bhattacharya, Dr Enrico Dall’Ara or Prof. Visakan Kadirkamanathan with “BONEsFE PhD studentship” in the title.