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Inflammation and mechanical loading in osteoarthritis: an integrative multi-scale approach
We have one vacancy for a bright, enthusiastic, self motivated PhD student to join the Department of Mechanical Engineering and the INSIGNEO Institute for in silico Medicine at the University of Sheffield.
Research project:
Osteoarthritis (OA) is a chronic disease affecting the joints, with the knee being one of the joints most commonly affected. Although excessive mechanical loading, in particular in obese people, contributes greatly to its onset, OA is now seen as a multifactorial disorder in which low-grade, chronic inflammation has a central role. This project will create a novel computational platform for the study of OA by combining for the first time (1) weight and physical activity as mechanical loading factors and (2) obesity and nutritional factors with the release of cytokines and adipocytes from the surrounding adipose tissue of the joint. The main aim is to develop a spatial and temporal multiscale computational approach that describes the interactions between the molecular pathways related to joint inflammation and the daily physical loading that contributes to cartilage and bone damage within the joint. This approach is a new departure towards the modelling of systemic changes resulting from several inflammation-related factors.
State-of-the-art biomechanical finite element (FE) models will be coupled with non-linear ordinary differential equations (ODE) describing the pro- and anti-inflammatory activities within the knee joint. A set of ODEs will describe the concentration over time of pro- and anti-inflammatory molecules available from the surrounding adipose tissue. The simulation of cartilage and subchondral bone degradation over time through the production of enzymes released by macrophages and overloading of the cartilage and subchondral bone will be modelled. The complex time interaction between the FE and the ODE model makes this task particularly challenging. The overall modelling platform will be adapted to enable testing the predictive capability of OA onset and development under clinical setting.
Conditions and requirements:
This studentship will be supervised by Professor Damien Lacroix. The successful candidate should have or be expected to obtain a 1st class or a good 2.1 degree in mechanical engineering, bioengineering, physics, applied mathematics or computer science, and should be enthusiastic about fundamental research. Previous knowledge on numerical methods such as finite element analysis and programming skills are essential.
This studentship funded by the University of Sheffield will start on 1 October 2022 and will cover student tuition fees, living expenses (at current EPSRC rates, £15,609 in 2021/22 per annum) and approximately £4k for other costs (experiments, conferences, etc). The studentship will last for 42 months.
To apply, please send to Prof. Damien Lacroix: D.Lacroix@sheffield.ac.uk a motivation letter (limited to 1 A4 page) together with your CV and two references before 28 February 2022.
Online interviews with short-listed candidates are expected to take place on 8 March 2022.
Academic environment:
Mechanical Engineering has been a major discipline in the University of Sheffield since its foundation in 1905 and is a thriving department within the University’s Faculty of Engineering. We are one of the UK’s leading departments of Mechanical Engineering, and are home to over 1000 students (Undergraduate, Postgraduate Taught and Postgraduate Research). We have over 60 academic members of staff, over 50 researchers, almost 40 members of administrative staff and 29 technicians. 2022 is an exciting time to join the department of Mechanical Engineering as we have recently moved into our £50m home – the Engineering Heartspace!
The Insigneo Institute for in silico Medicine is a collaboration between the Faculties of Engineering, Medicine, Dentistry and Health and Science at University of Sheffield, Sheffield Teaching Hospitals NHS Foundation Trust and Sheffield Children’s Hospital. Established in 2012, the Institute has built a strong multidisciplinary network of over 260 academics and clinicians who bring together expertise in biomedical imaging, healthcare data, computational modelling, and digital healthcare technologies.
The Institute aims to drive innovative research at the interface of healthcare, engineering and science to transform the future of healthcare technology. The Institute focuses on shaping technology enhanced healthcare, increasing clinical impact through technological approaches, leading on computational and technological healthcare research in partnership with the NHS and industry.
Our research is centred around five main themes - Computational modelling in medicine, Biomaterials/Biomechanics/Cell engineering, Biomedical Imaging, Smart devices and sensors and Healthcare data/AI. Led by Research Theme directors the aim is to develop and lead on our research strategy, build collaborations and networks both within and external to the University. For more information on INSIGNEO please see our web pages: https://www.sheffield.ac.uk/insigneo
We have one vacancy for a bright, enthusiastic, self motivated PhD student to join the Department of Mechanical Engineering and the INSIGNEO Institute for in silico Medicine at the University of Sheffield.
Research project:
Osteoarthritis (OA) is a chronic disease affecting the joints, with the knee being one of the joints most commonly affected. Although excessive mechanical loading, in particular in obese people, contributes greatly to its onset, OA is now seen as a multifactorial disorder in which low-grade, chronic inflammation has a central role. This project will create a novel computational platform for the study of OA by combining for the first time (1) weight and physical activity as mechanical loading factors and (2) obesity and nutritional factors with the release of cytokines and adipocytes from the surrounding adipose tissue of the joint. The main aim is to develop a spatial and temporal multiscale computational approach that describes the interactions between the molecular pathways related to joint inflammation and the daily physical loading that contributes to cartilage and bone damage within the joint. This approach is a new departure towards the modelling of systemic changes resulting from several inflammation-related factors.
State-of-the-art biomechanical finite element (FE) models will be coupled with non-linear ordinary differential equations (ODE) describing the pro- and anti-inflammatory activities within the knee joint. A set of ODEs will describe the concentration over time of pro- and anti-inflammatory molecules available from the surrounding adipose tissue. The simulation of cartilage and subchondral bone degradation over time through the production of enzymes released by macrophages and overloading of the cartilage and subchondral bone will be modelled. The complex time interaction between the FE and the ODE model makes this task particularly challenging. The overall modelling platform will be adapted to enable testing the predictive capability of OA onset and development under clinical setting.
Conditions and requirements:
This studentship will be supervised by Professor Damien Lacroix. The successful candidate should have or be expected to obtain a 1st class or a good 2.1 degree in mechanical engineering, bioengineering, physics, applied mathematics or computer science, and should be enthusiastic about fundamental research. Previous knowledge on numerical methods such as finite element analysis and programming skills are essential.
This studentship funded by the University of Sheffield will start on 1 October 2022 and will cover student tuition fees, living expenses (at current EPSRC rates, £15,609 in 2021/22 per annum) and approximately £4k for other costs (experiments, conferences, etc). The studentship will last for 42 months.
To apply, please send to Prof. Damien Lacroix: D.Lacroix@sheffield.ac.uk a motivation letter (limited to 1 A4 page) together with your CV and two references before 28 February 2022.
Online interviews with short-listed candidates are expected to take place on 8 March 2022.
Academic environment:
Mechanical Engineering has been a major discipline in the University of Sheffield since its foundation in 1905 and is a thriving department within the University’s Faculty of Engineering. We are one of the UK’s leading departments of Mechanical Engineering, and are home to over 1000 students (Undergraduate, Postgraduate Taught and Postgraduate Research). We have over 60 academic members of staff, over 50 researchers, almost 40 members of administrative staff and 29 technicians. 2022 is an exciting time to join the department of Mechanical Engineering as we have recently moved into our £50m home – the Engineering Heartspace!
The Insigneo Institute for in silico Medicine is a collaboration between the Faculties of Engineering, Medicine, Dentistry and Health and Science at University of Sheffield, Sheffield Teaching Hospitals NHS Foundation Trust and Sheffield Children’s Hospital. Established in 2012, the Institute has built a strong multidisciplinary network of over 260 academics and clinicians who bring together expertise in biomedical imaging, healthcare data, computational modelling, and digital healthcare technologies.
The Institute aims to drive innovative research at the interface of healthcare, engineering and science to transform the future of healthcare technology. The Institute focuses on shaping technology enhanced healthcare, increasing clinical impact through technological approaches, leading on computational and technological healthcare research in partnership with the NHS and industry.
Our research is centred around five main themes - Computational modelling in medicine, Biomaterials/Biomechanics/Cell engineering, Biomedical Imaging, Smart devices and sensors and Healthcare data/AI. Led by Research Theme directors the aim is to develop and lead on our research strategy, build collaborations and networks both within and external to the University. For more information on INSIGNEO please see our web pages: https://www.sheffield.ac.uk/insigneo