Vacancies
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Current vacancies
PhD Opportunity: Improving oxygen monitoring technology for young children and infants
Closing date: 17 May 2024
Employer: The University of Sheffield (Department of Automatic Control and Systems Engineering)
Location: Sheffield
About the Project
Measuring oxygen levels in children is crucial, often considered as important as monitoring other vital signs like heart rate and temperature. However, doing so in infants and pre-schoolers outside of hospitals can be challenging.
Guidelines at both national and international levels suggest checking oxygen levels in primary care for children with respiratory issues to help decide if they need to be referred to a specialist. However, there's concern that the technology used for these measurements might be leading to unnecessary diagnoses, resulting in more hospital admissions for conditions like bronchiolitis in infants.
Surprisingly, the ability to monitor oxygen levels in children is not widely available in regular doctor's offices, even though respiratory infections are a common reason for children to visit primary care.
Finding simpler and more reliable methods to measure oxygen levels in children could not only improve decision-making in regular healthcare settings but could also be a valuable tool for monitoring at home, especially during potential respiratory pandemics. This issue is not just relevant to well-resourced areas but is also crucial in places where resources are limited, as pneumonia remains a leading cause of death in young children.
Aim
We will develop a smart material, e.g., fabric, sticker, as a custom interactive physical interface to improve sensing readings for oxygen measurements acquired at the tip of infants' and children's fingers, by finding suitable and seamless ways to engage the children in this process.
Key objectives
We will begin by conducting initial trials with children to examine different items like objects, fabrics, and toys. The goal is to figure out which interfaces could be effectively incorporated into a custom oxygen measurement device.
We'll work on developing a physical interface using electro-luminescence, inspired by the principles of oximeters, to enhance the accuracy of oxygen measurements. This interface also needs to fit well with how children naturally interact. The interface will be tested in real-world conditions, considering factors like flexion, bending, and stretching, while also assessing its performance on the smaller fingers of children.
Next, we'll implement an active interface to improve the sensing capabilities, along with setting up the necessary tools for data acquisition and ensuring portability.
To make the device engaging for a wide range of ages, we'll create various interfaces and evaluate their effectiveness with different age groups.
This project will give you the opportunity to work alongside patients, families, clinicians, engineers, and other experts in a pioneering cross-disciplinary programme to develop new digital platforms and technologies that can address unmet needs in child health.
This is a unique opportunity to be at the forefront of innovative developments in the field of paediatric digital healthcare technology and to make change happen for the better.
As a member of our team, you will receive training in fabricating flexible interfaces and functional materials, as well as the principles of wearables. These skills form the core of our laboratory's expertise. Our work on medical robots has garnered significant attention from both mainstream and specialised media outlets, including Forbes, The Economist, New Scientist, The Telegraph, and USA Today. National Geographic recognised our medical robots as one of the 12 Innovations that will revolutionise medicine in 2019, and Scientific American highlighted our work among the 10 Ideas that will change the world in 2016.
This project is a collaboration between Great Ormond Street Hospital for Children NHS Foundation Trust, Sheffield Children’s NHS Foundation Trust, the NIHR Children and Young People MedTech Co-operative, and the Insigneo Institute at the University of Sheffield.
Now it’s in its fourth 5-year term, a BRC National Paediatric Excellence Initiative has been set up between GOSH BRC and the children’s hospitals in Birmingham, Sheffield, and Liverpool. The GOSH BRC’s aim is to transform the health of children, and the adults they will become, by combining cutting-edge research methods with world-leading clinical trial expertise, to accelerate the discovery of new treatments for children with rare and complex conditions.
More information can be found here: https://sites.google.com/site/danadamian
Entry requirements
Candidates are expected to have a background in one of the following fields: Mechanical Engineering, Robotics, Mechatronics, Electrical Engineering, Material Engineering, Bioengineering, Control, or a related field. Applicants should have, or expect to achieve a first or upper second class UK honours degree or equivalent qualifications gained outside the UK in an appropriate area of study.
How to apply
Please complete a University Postgraduate Research Application form available here: www.shef.ac.uk/postgraduate/research/apply
Please clearly state the prospective main supervisor Dr Dana Damian in the respective box and select Automatic Control & Systems Engineering as the department.
Enquiries
Pre-application and informal enquiries accompanied by a CV are encouraged to contact Sarah Black (Insigneo Administrative Manager, sarah.black@sheffield.ac.uk).
If you have questions about the project, feel free to email Dr Dana Damian (Primary Supervisor, d.damian@sheffield.ac.uk).
Funding Notes
Funding is provided for home tuition fees only and a stipend (£18,622) for three years. Overseas tuition fees are not covered.
Funding is provided by the Insigneo Institute, Sheffield Children’s NHS Foundation Trust and NIHR GOSH Biomedical Research Centre (BRC) as part of their National Paediatric Excellence Initiative. The NIHR GOSH BRC (GOSH BRC) is a partnership between GOSH and the University College London (UCL) GOSH Institute of Child Health (ICH).
Research Associate in preclinical musculoskeletal imaging and biomechanics
Closing date: 4 June 2024
Employer: The University of Sheffield (School of Medicine and Population Health)
Location: Sheffield
Salary: £37,099 - £45,585 per annum
Vacancy number: UOS040932
This highly interdisciplinary Research Associate position will advance our understanding of the effect of biomechanical and pharmacological treatments for Osteoporosis (OP) in a mouse model. The position is within Insigneo and is funded as part of a project selected by the ERC-Consolidator and funded by the EPSRC that aims to develop and validate new multiscale computational models for optimising treatments for OP. This part of the project is focused on the collection of experimental and imaging data to inform and validate the models.
The ideal candidate will have an excellent PhD in musculoskeletal imaging, biomechanics or a related discipline. They will possess a solid knowledge of bone and muscle imaging and experience with in vivo mouse experiments. Ensuring the achievement of the project objectives will advance the vision of the Insigneo Institute to validate computational models for the musculoskeletal system and produce a transformational impact on healthcare. The Research Associate will also sustain and strengthen collaboration within relevant Insigneo research groups and beyond; and will commit to Insigneo’s mission to produce high quality and impactful cutting-edge research.
The successful candidate will develop microCT and microMRI in vivo imaging approaches to measure longitudinally the properties of bones and muscles in mice. They will also establish a mouse gait laboratory for the 3D longitudinal assessment of movement in mice. These approaches will be used to measure the effect of Osteoporosis and related treatment on the musculoskeletal health and mobility and to inform and validate computational models of bone adaptation developed within the team.
The Research Associate will work collaboratively with other colleagues within the IMSB group, the SkeletAl laboratory, and the Insigneo Institute to validate the first inter-species (mouse and human) virtual twin for optimising treatments for Osteoporosis.
We’re one of the best not-for-profit organisations to work for in the UK. The University’s Total Reward Package includes a competitive salary, a generous Pension Scheme and annual leave entitlement, as well as access to a range of learning and development courses to support your personal and professional development.
We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience.
How to apply
To apply visit our job pages (https://www.sheffield.ac.uk/jobs) and search for vacancy number: UOS040932.
Contact details
For informal enquiries about this job contact Enrico Dall’Ara, Prof Musculoskeletal Biomechanics, Head of the Integrative Musculoskeletal Biomechanics (IMSB) group and Director of the SkeletAl laboratory on: e.dallara@sheffield.ac.uk
Research Associate in computational musculoskeletal biomechanics
Closing date: 4 June 2024
Employer: The University of Sheffield (School of Medicine and Population Health)
Location: Sheffield
Salary: Grade 7, £37,099 - £45,585 per annum
Vacancy number: UOS040929
Are you interested in developing the first Virtual Mouse Twin for the optimisation of treatments for Osteoporosis?
This highly interdisciplinary Research Associate position will advance our understanding of the effect of the combined biomechanical and pharmacological treatments on musculoskeletal biomechanics using mouse models, personalised multibody dynamics models, and subject specific finite element models.
The position is within the Insigneo Institute and is funded as part of a project selected by the ERC-Consolidator and funded by the EPSRC that aims to develop and validate new multiscale computational models for optimising treatments for OP. This part of the project is focused on the development and integration of personalised multibody dynamics models of the mouse hindlimb and finite element models of the mouse tibia. These models will be the basis for the virtual mouse twin, that will be used to test new interventions against Osteoporosis in silico.
The ideal candidate will have an excellent PhD in computational musculoskeletal biomechanics or a related discipline. They will possess a solid knowledge of bone and muscle biomechanics, multibody dynamics models, and finite element models for bones. Ensuring the achievement of the project objectives will advance the vision of the Insigneo institute to validate computational models for the musculoskeletal system and produce a transformational impact on healthcare. The Research Associate will also sustain and strengthen collaboration within relevant Insigneo research groups and beyond; and will commit to Insigneo’s mission to produce high quality and impactful cutting-edge research.
We’re one of the best not-for-profit organisations to work for in the UK. The University’s Total Reward Package includes a competitive salary, a generous Pension Scheme and annual leave entitlement, as well as access to a range of learning and development courses to support your personal and professional development.
We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience.
How to apply
To apply visit our job pages (https://www.sheffield.ac.uk/jobs) and search for vacancy number: UOS040929.
Contact details
For informal enquiries about this job contact Enrico Dall’Ara, Prof Musculoskeletal Biomechanics, Head of the Integrative Musculoskeletal Biomechanics (IMSB) group and Director of the SkeletAl laboratory on: e.dallara@sheffield.ac.uk
Research Technician
Closing date: 4 June 2024
Employer: The University of Sheffield (School of Medicine and Population Health)
Location: Sheffield
Salary: Grade 5, £25,742 to £29,605 per annum
Vacancy number: UOS040930
We have an exciting opportunity in the Division of Clinical Medicine of the University of Sheffield for a Research Technician with a passion in laboratory work, musculoskeletal research, and training people in using our state-of-the art kits!
We are seeking candidates with degree in physics or a biological subject or relevant area, as well as previous experience of experimental work. As this role involves supporting in vivo and ex vivo experimental work with X-ray micro-computed tomography, magnetic resonance imaging, gait analysis, histology and immunohistochemistry, you will have experience at least in some of these techniques.
You will join the SkeletAl laboratory with experts of bone imaging and analyses, helping local, national and international customers to obtain the most accurate research results. You will work in a well-connected team of technicians and academics with world-leading reputations in characterising bone from different analyses (imaging, histology, biomechanics, etc.). Take a look at our website for more details: http://skeletal.group.shef.ac.uk/! In this varied and dynamic role, you will be responsible for maintaining and developing procedures for imaging at high resolution different materials and training customers to use our machines. Working alongside laboratory members with different skills, the role will offer you an opportunity to learn about several lab techniques.
You will join also the group of Prof. Enrico Dall’Ara. Our biomechano-imaging group has an international and interdisciplinary profile and a strong commitment to clinical and industrial translation with impact in future healthcare. We are active in imaging and biomechanics of the skeletal systems and we have access to different experimental, imaging and computational facilities.
You will work together with other members of the team to characterise the effect of different treatments for Osteoporosis on mice musculoskeletal health. You will work together with a postdoctoral researcher to develop in vivo imaging approaches to measure longitudinally the properties of bones and muscles in mice. You will also establish a mouse gait laboratory for the 3D longitudinal assessment of movement in mice.
We’re one of the best not-for-profit organisations to work for in the UK. The University’s Total Reward Package includes a competitive salary, a generous Pension Scheme and annual leave entitlement, as well as access to a range of learning and development courses to support your personal and professional development.
We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience.
How to apply
To apply visit our job pages (https://www.sheffield.ac.uk/jobs) and search for vacancy number: UOS040930.
Contact details
For informal enquiries about this job contact Enrico Dall’Ara, Prof Musculoskeletal Biomechanics, Head of the Integrative Musculoskeletal Biomechanics (IMSB) group and Director of the SkeletAl laboratory on: e.dallara@sheffield.ac.uk
PhD Opportunity: A biochemo-mechano multi-scale computational model to predict bone adaptation over space and time
Closing date: 10 June 2024
Employer: The University of Sheffield (School of Medicine and Population Health)
Location: Sheffield
About the Project
Musculoskeletal diseases as osteoporosis have huge impact on the mortality and morbidity of our ageing society. At the moment there are some pharmacological interventions for treating osteoporosis but they are not effective in all patients and their cost is very high. New interventions have to be tested in animal models before clinical studies, the mouse being one of the most used models. Nevertheless, animal alternatives such as advanced in vitro (e.g. cell cultures, organ on a chip methods) and in silico approaches (i.e. computational modelling and digital twins) can improve the design and testing of new interventions and partially replace animal experimentation. Bone adapts over time and space thanks to the activity of the bone cells, which are triggered by biomechanical (e.g. mechanical loading or disuse) and biochemical (e.g. diseases or pharmacological treatments) stimulation. Therefore, the bone adaptation process is very complex as it involves different dimensional scales: the mechanical loading the bone is subjected to due to external forces (body level), the deformation the bone is subjected to under those forces (organ-tissue level) and the mechanical and biochemical stimuli that the cells feel (cell levels).
The Finite Element approach based on biomedical images can be used to estimate accurately how bone deforms under external loads [1]. Biological networks based on Ordinary Differential Equations have been used to estimate how biochemical stimuli affects bone adaptation [2]. Nevertheless, these two approaches have not yet been combined into a multi-scale model to predict bone adaptation over time. This is due to the fact that it is challenging to combine these two approaches and it is even harder to validate the outputs of the models (i.e. compare with experimental data that measure the bone adaptation over time). In our groups we have collected longitudinal high-resolution images of bone adaptation over time in a mouse model treated with biomechanical and/or pharmacological interventions [3], providing the best validation datasets for the validation of the multi-scale models. Moreover, we have shown that mechano-regulation models (i.e. models that consider explicitly only biomechanical stimuli) can predict reasonably well only bone adaptation [4]. The hypothesis of this project is that multi-scale computational models that account for both biomechanical and biochemical stimuli can accurately predict bone changes over space and time due to different treatments. The project aims at developing the first multi-scale biomechanical model for the prediction of bone changes over time in the mouse tibia due to external biomechanical and biochemical stimuli, and at validating its outcomes versus state-of-the-art longitudinal micro-computed tomography (microCT) measurements of bone adaptation. The student will first perform a literature review and will be trained to use the finite element modelling approaches available at the supervisors’ teams. Then they will develop cell-level biological networks for the prediction of the changes in molecular and cellular concentrations over time due to biochemical stimuli and will integrate them with the finite element models. They will perform model verification and sensitivity analysis to identify the most important sensitive input parameters in the models. They will validate the models versus experimental measurements performed with in vivo longitudinal microCT imaging of the mouse tibia, in mice treated with pharmacological and/or biomechanical interventions. The student will evaluate the importance of accounting for mechanical and/or biochemical stimuli for the accurate prediction of bone changesdue to interventions. Finally, the student will focus on scientific publications and writing the thesis. The project will generate academic impact (using the model to test new hypothesis and the effect of combined treatments), industrial impact (for companies that develop treatments for the musculoskeletal system), and 3Rs impact (reduction and partial replacement of the usage ofanimals in research).
How to apply:
Please complete a University Postgraduate Research Application form available here: http://www.shef.ac.uk/postgraduate/research/apply.
Please clearly state the prospective main supervisor (Prof Enrico Dall’Ara) in the respective box and select SMPH Oncology and Metabolism as the department.
Funding Notes
Candidates must have a first or upper second class honors degree or significant research experience. Degree in Engineering, Physics, Mathematics or equivalent.
This studentship funded by the University of Sheffield will be 42 months in duration, and include home fee for students, stipend at UKRI rates, a research training support grant (RTSG) of £4,400. International student are welcome to apply only if they will have already co-funding for the difference between international and home fees. Overseas fees information is available on the website:
Fees for Academic Year 2024-25: View Website
PhD Opportunity: Biomechanics of internal fixation methods for ankle fusion
Closing date: 18 June 2024
Employer: The University of Sheffield (Department of Mechanical Engineering)
Location: Sheffield
About the Project
Ankle fusion is a common treatment for advanced ankle arthritis to relieve pain and improve functional outcomes. However, there is a reported non-union rate of 5-37%, requiring further surgery or an ankle replacement. Moreover, there are several options for internal fixation, with no consensus on the number of screws, orientations, and placement in ankle fusion surgery.
This project aims to develop validated computational models of the foot and ankle, and investigate the biomechanical parameters impacting successful bone healing while reducing the risk of fixation failure.
The project will involve parametric analysis of participants’ data, finite element analysis and mechanical testing. Hence, the candidate will be consulting with collaborators in orthopaedic surgery, bioengineering, mechanical engineering and the Insigneo Institute. The candidate will gain a unique opportunity to carry out research in an exciting interdisciplinary project to answer important clinical questions.
Requirements
We are looking for applicants who are eager to develop new skills and apply their existing knowledge. You should be excited to learn and develop new technology, be passionate about the subject and look to be creative in your work. In addition, you should:
- Hold (or will receive this year) a master's degree (or equivalent, e.g. MEng) at merit/distinction level, or a first class/ upper second (2:1) class honours degree in biomedical engineering, mechanical engineering, applied maths or a related field.
- Proficiency in finite element analysis software (e.g., Abaqus, Ansys etc) and programming languages such as Python, MATLAB etc.
- Strong analytical and problem-solving skills.
- Good interpersonal and organisational skills, and the ability to work as a team player.
Interested candidates are strongly encouraged to contact Dr Vee San Cheong (v.cheong@sheffield.ac.uk), to discuss your interest in and suitability for the project prior to submitting your application.
Funding Notes
This studentship includes a fee bursary to cover the UK (home) rate, and an annual tax-free maintenance stipend at the standard UK Research rate (£19,237 in 2024-25) for up to 3.5 years. Overseas applicants will need to secure additional funding to cover the difference in fees, or with their own funds which is approximately £22,884 per year. Overseas applicants should ensure they can pay the difference in fees prior to applying or sending any enquiries.
PhD Opportunity: Efficient in silico trials for bone diseases
Closing date: 28 June 2024
Employer: The University of Sheffield (Department of Mechanical Engineering)
Location: Sheffield
About the Project
The School of Mechanical, Aerospace and Civil Engineering at the University of Sheffield is recruiting for a PhD position associated with the EPSRC funded New Investigator Award BONESFE. The position will be based within the Integrated Musculo-Skeletal Biomechanics Group in the Insigneo Institute for in silico Medicine, a collaboration between the University of Sheffield, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield Children's NHS Foundation Trust and Doncaster and Bassetlaw Teaching Hospitals NHS Foundation Trust.
This project is concerned with the exciting new area of In Silico Trials. In Silico Trials aim to predict the safety and efficacy of medical interventions (i.e. devices and drugs), which are necessary to obtain regulatory approval such that these interventions can be brought to market. At the same time, In Silico Trials need fewer patients and/or shorter trial durations than conventional clinical trials and can reduce the cost to enter the market for much-needed medical products.
With a focus on bone diseases and drugs and devices used to treat them, the project will leverage recent advances in the characterisation of bone shape variation in a population and in the development of intrusive stochastic finite-element analysis tools. The overall aim of the project is to improve the efficiency and reduce the cost of conducing In Silico Trials, thus encouraging uptake of this technology by device and drug manufacturers.
We are looking for applicants who are eager to develop new skills and apply their existing knowledge. The project requires a good level of mathematical and solid mechanics background and will require the candidate to develop and extend existing finite-element code and execute it on high-performance computing systems. You should be excited to learn and develop new technology, be passionate about the subject and look to be creative in your work.
Applicants should hold or be completing this year a degree at a good level (2.1/1st or equivalent) in a related subject, e.g. engineering, physics, maths, computer science, and should be able to demonstrate good interpersonal and organisational skills. The expected start date for this project is September 2024.
Interested candidates are strongly encouraged to contact the project supervisor, Dr Pinaki Bhattacharya (p.bhattacharya@sheffield.ac.uk) to discuss your interest in and suitability for the project prior to submitting your application.
To apply, please use our on-line PhD application form
Funding Notes
The funding for this opportunity includes fees set for UK (Home) applicants and a tax-free stipend of £19,237 per year, up to 3.5 years. Overseas applicants will need to cover the difference in fees from their own funds which is approximately £22,884 per year. Overseas applicants should ensure they can pay the difference in fees prior to applying or sending any enquiries.
