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Current vacancies

• The Sheffield Children’s Hospital/Insigneo Institute for In Silico Medicine PhD Programme in Digital Health: Digital Healthcare at Home

• The Sheffield Children’s Hospital/Insigneo Institute for In Silico Medicine PhD Programme in Digital Health: Digital Wards

• The Sheffield Children’s Hospital/Insigneo Institute for In Silico Medicine PhD Programme in Digital Health: Advanced Healthcare Communication

• The Sheffield Children’s Hospital/Insigneo Institute for In Silico Medicine PhD Programme in Digital Health: Digital Twins

• EPSRC Doctoral Training Partnership: A computational biomechanical model to optimise personalised treatments for spine metastases

The Sheffield Children’s Hospital/Insigneo Institute for In Silico Medicine PhD Programme in Digital Health: Digital Healthcare at Home

About the Project

Supervisor(s): 

Professor Jim Wild (representing a team of potential supervisors from Insigneo) and Professor Paul Dimitri (representing a team of potential supervisors from SCH)

Sheffield Children’s Hospital, the NIHR Children and Young People MedTech Cooperative and the Insigneo Institute for In Silico Medicine at the University of Sheffield are recruiting up to 4 PhD studentships in Paediatric Digital Healthcare Technology, this PhD is specifically looking at Digital Healthcare at Home.

Successful applicants will work together in a pioneering cross-disciplinary programme alongside patients, families, clinicians, engineers, computer scientists and other experts to develop new digital platforms and technologies that can address unmet needs in child health. This research will focus on paediatric clinical care pathways and span the Insigneo research themes of Healthcare Data, Artificial Intelligence and Smart Devices and Sensors. It will develop the concepts of Digital Twins, Digital Wards, Digital Healthcare at Home and Advanced Healthcare Communication in paediatric real life healthcare settings with Sheffield Children’s Hospital and in collaboration with Great Ormond Street Hospital.

Each project will follow three stages.

Stage 1

Each project will work with clinicians, patients and families in a series of workshops to identify a specific clinical problem in disease areas such as respiratory disease, neurology, musculoskeletal disease and mental health that could be improved by capture and transfer of digital data from current or newly developed sensors and other technologies used by the patient and or their family at home and in daily life.

Stage 2

Projects will then work with academic teams of engineers and industrial partners to develop prototype technologies required to obtain the data identified in Stage 1 and the secure IT and telecommunication infrastructure required to present the data to the patient/family and the clinical team. Iterative co-design will optimise technology and interface design.

Stage 3

Once technologies and digital infrastructures are established, projects will work with patients/families and clinicians to design novel care pathways that use the data generated to; a) optimise frequency of remote or in-person clinical review b) alter treatment decisions c) create efficient healthcare delivery with minimal intrusion.

Successful completion will lead to functional data capture and exchange platforms and a proposed clinical pathway for each clinical problem and its technological solution. These will be at the point of readiness for follow on clinical studies testing their ability to improve outcomes such as patient/family satisfaction, patient-reported outcomes, reduction of hospital visits/admissions, and clinical outcomes compared with current standard-of-care.

Applicants must be highly motivated, adaptable, willing to learn skills from a wide range of areas and able to work in a cross-disciplinary team. Applications are welcomed from a wide range of disciplines including engineering, computer science, healthcare professions and other backgrounds. A practical interest in the integration of digital healthcare data from both bespoke sensors and ubiquitous smart devices with specific computational infrastructure is needed. An upper second class degree at undergraduate level is required and previous experience in research is desirable.

Each project’s supervisory team will include one clinician from Sheffield Children’s Hospital and up to two academic members of the Insigneo Institute, University of Sheffield. Supervisors will be allocated to suit the specifics of the research and may change from those stated.

Entry Requirements:

Candidates must have a first or upper second class honours degree or significant research experience. A practical interest in the integration of digital healthcare data from both bespoke sensors and ubiquitous smart devices with specific computational infrastructure is needed.

The ideal student will have:

• Academic Background: Applicants should have a strong academic background in a relevant discipline such as engineering, computer science, mathematics, physics, healthcare, or another related field.
• Research Experience: Applicants should have prior research experience, ideally in a related area. This could include experience gained through previous research projects, internships, or work experience.
• Interdisciplinary Skills: The PhD program requires working in a highly interdisciplinary environment, so applicants should have strong interdisciplinary skills and be able to work well with people from different backgrounds and disciplines.
• Technical Skills: Applicants should have good technical skills, including knowledge of programming languages, software tools, and statistical analysis techniques. They should also have a good understanding of digital technologies and their potential applications in healthcare.
• Communication Skills: Applicants should have excellent communication skills, both written and verbal. They should be able to explain their research clearly and effectively to a range of audiences, including healthcare professionals, patients, and other stakeholders.
• Motivation and Enthusiasm: Applicants should be highly motivated and enthusiastic about the research area and have a strong interest in making a meaningful contribution to child health.
• Eligibility: Applicants should meet the eligibility requirements for PhD study at the University of Sheffield. This typically includes having a good undergraduate degree and meeting the English language proficiency requirements

Enquiries:

Pre-application and informal enquiries accompanied by a CV are encouraged to Sarah Black (Insigneo Administrative Manager) sarah.black@sheffield.ac.uk

Funding: 

Funding for these PhDs is provided by the NIHR Great Ormond Street Biomedical Research Centre and Sheffield Children’s NHS Foundation Trust as part of their Paediatric Excellence Initiative. The NIHR Great Ormond Street Hospital BRC (GOSH BRC) is a partnership between Great Ormond Street Hospital and the University College London (UCL) Great Ormond Street Institute of Child Health (ICH). Now it’s in its fourth 5-year term, as part of a wider national collaboration - a BRC National Paediatric Excellence Initiative has been set up between GOSH BRC and children’s hospitals in Birmingham, Sheffield and Liverpool. 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 discovery of new treatments for children with rare and complex conditions.

Funding Notes

Salary/stipend rate:

• The UKRI doctoral stipend for 2022/23 - £17,668 full time equivalent per annum
• Project expenses – up to £500 per annum
• Home student tuition fees will be covered. Overseas students will be required to cover the financial shortfall between home and overseas student fees.

Proposed start date: 4th September 2023

The Sheffield Children’s Hospital/Insigneo Institute for In Silico Medicine PhD Programme in Digital Health: Digital Wards

About the Project

Supervisor(s): 

Professor Jim Wild (representing a team of potential supervisors from Insigneo) and Professor Paul Dimitri (representing a team of potential supervisors from SCH)

Sheffield Children’s Hospital, the NIHR Children and Young People MedTech Cooperative and the Insigneo Institute for In Silico Medicine at the University of Sheffield are recruiting up to 4 PhD studentships in Paediatric Digital Healthcare Technology, this PhD is specifically looking at Digital Wards.

Successful applicants will work together in a pioneering cross-disciplinary programme alongside patients, families, clinicians, engineers, computer scientists and other experts to develop new digital platforms and technologies that can address unmet needs in child health. This research will focus on paediatric clinical care pathways and span the Insigneo research themes of Healthcare Data, Artificial Intelligence and Smart Devices and Sensors. It will develop the concepts of Digital Twins, Digital Wards, Digital Healthcare at Home and Advanced Healthcare Communication in paediatric real life healthcare settings with Sheffield Children’s Hospital and in collaboration with Great Ormond Street Hospital.

Each project will follow three stages.

Stage 1

Each project will work with clinicians, patients and families in a series of workshops to identify a specific clinical problem in disease areas such as respiratory disease, neurology, musculoskeletal disease and mental health that could be improved by capture and transfer of digital data from current or newly developed sensors and other technologies used by the patient and or their family at home and in daily life.

Stage 2

Projects will then work with academic teams of engineers and industrial partners to develop prototype technologies required to obtain the data identified in Stage 1 and the secure IT and telecommunication infrastructure required to present the data to the patient/family and the clinical team. Iterative co-design will optimise technology and interface design.

Stage 3

Once technologies and digital infrastructures are established, projects will work with patients/families and clinicians to design novel care pathways that use the data generated to; a) optimise frequency of remote or in-person clinical review b) alter treatment decisions c) create efficient healthcare delivery with minimal intrusion.

Successful completion will lead to functional data capture and exchange platforms and a proposed clinical pathway for each clinical problem and its technological solution. These will be at the point of readiness for follow on clinical studies testing their ability to improve outcomes such as patient/family satisfaction, patient-reported outcomes, reduction of hospital visits/admissions, and clinical outcomes compared with current standard-of-care.

Applicants must be highly motivated, adaptable, willing to learn skills from a wide range of areas and able to work in a cross-disciplinary team. Applications are welcomed from a wide range of disciplines including engineering, computer science, healthcare professions and other backgrounds. A practical interest in the integration of digital healthcare data from both bespoke sensors and ubiquitous smart devices with specific computational infrastructure is needed. An upper second class degree at undergraduate level is required and previous experience in research is desirable.

Each project’s supervisory team will include one clinician from Sheffield Children’s Hospital and up to two academic members of the Insigneo Institute, University of Sheffield. Supervisors will be allocated to suit the specifics of the research and may change from those stated.

Entry Requirements:

Candidates must have a first or upper second class honours degree or significant research experience. A practical interest in the integration of digital healthcare data from both bespoke sensors and ubiquitous smart devices with specific computational infrastructure is needed.

The ideal student will have:

• Academic Background: Applicants should have a strong academic background in a relevant discipline such as engineering, computer science, mathematics, physics, healthcare, or another related field.
• Research Experience: Applicants should have prior research experience, ideally in a related area. This could include experience gained through previous research projects, internships, or work experience.
• Interdisciplinary Skills: The PhD program requires working in a highly interdisciplinary environment, so applicants should have strong interdisciplinary skills and be able to work well with people from different backgrounds and disciplines.
• Technical Skills: Applicants should have good technical skills, including knowledge of programming languages, software tools, and statistical analysis techniques. They should also have a good understanding of digital technologies and their potential applications in healthcare.
• Communication Skills: Applicants should have excellent communication skills, both written and verbal. They should be able to explain their research clearly and effectively to a range of audiences, including healthcare professionals, patients, and other stakeholders.
• Motivation and Enthusiasm: Applicants should be highly motivated and enthusiastic about the research area and have a strong interest in making a meaningful contribution to child health.
• Eligibility: Applicants should meet the eligibility requirements for PhD study at the University of Sheffield. This typically includes having a good undergraduate degree and meeting the English language proficiency requirements

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 in the respective box and select Department of Infection, Immunity & Cardiovascular Science as the department.

Enquiries:

Pre-application and informal enquiries accompanied by a CV are encouraged to Sarah Black (Insigneo Administrative Manager) sarah.black@sheffield.ac.uk

Funding: 

Funding for these PhDs is provided by the NIHR Great Ormond Street Biomedical Research Centre and Sheffield Children’s NHS Foundation Trust as part of their Paediatric Excellence Initiative. The NIHR Great Ormond Street Hospital BRC (GOSH BRC) is a partnership between Great Ormond Street Hospital and the University College London (UCL) Great Ormond Street Institute of Child Health (ICH). Now it’s in its fourth 5-year term, as part of a wider national collaboration - a BRC National Paediatric Excellence Initiative has been set up between GOSH BRC and children’s hospitals in Birmingham, Sheffield and Liverpool. 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 discovery of new treatments for children with rare and complex conditions.

Funding Notes

Salary/stipend rate:

• The UKRI doctoral stipend for 2022/23 - £17,668 full time equivalent per annum
• Project expenses – up to £500 per annum
• Home student tuition fees will be covered. Overseas students will be required to cover the financial shortfall between home and overseas student fees.

Proposed start date: 1 October 2023

The Sheffield Children’s Hospital/Insigneo Institute for In Silico Medicine PhD Programme in Digital Health: Advanced Healthcare Communication

About the Project

Supervisor(s): 

Professor Jim Wild (representing a team of potential supervisors from Insigneo) and Professor Paul Dimitri (representing a team of potential supervisors from SCH)

Sheffield Children’s Hospital, the NIHR Children and Young People MedTech Cooperative and the Insigneo Institute for In Silico Medicine at the University of Sheffield are recruiting up to 4 PhD studentships in Paediatric Digital Healthcare Technology, this PhD is specifically looking at Advanced Healthcare Communication.

Successful applicants will work together in a pioneering cross-disciplinary programme alongside patients, families, clinicians, engineers, computer scientists and other experts to develop new digital platforms and technologies that can address unmet needs in child health. This research will focus on paediatric clinical care pathways and span the Insigneo research themes of Healthcare Data, Artificial Intelligence and Smart Devices and Sensors. It will develop the concepts of Digital Twins, Digital Wards, Digital Healthcare at Home and Advanced Healthcare Communication in paediatric real life healthcare settings with Sheffield Children’s Hospital and in collaboration with Great Ormond Street Hospital.

Each project will follow three stages.

Stage 1

Each project will work with clinicians, patients and families in a series of workshops to identify a specific clinical problem in disease areas such as respiratory disease, neurology, musculoskeletal disease and mental health that could be improved by capture and transfer of digital data from current or newly developed sensors and other technologies used by the patient and or their family at home and in daily life.

Stage 2

Projects will then work with academic teams of engineers and industrial partners to develop prototype technologies required to obtain the data identified in Stage 1 and the secure IT and telecommunication infrastructure required to present the data to the patient/family and the clinical team. Iterative co-design will optimise technology and interface design.

Stage 3

Once technologies and digital infrastructures are established, projects will work with patients/families and clinicians to design novel care pathways that use the data generated to; a) optimise frequency of remote or in-person clinical review b) alter treatment decisions c) create efficient healthcare delivery with minimal intrusion.

Successful completion will lead to functional data capture and exchange platforms and a proposed clinical pathway for each clinical problem and its technological solution. These will be at the point of readiness for follow on clinical studies testing their ability to improve outcomes such as patient/family satisfaction, patient-reported outcomes, reduction of hospital visits/admissions, and clinical outcomes compared with current standard-of-care.

Applicants must be highly motivated, adaptable, willing to learn skills from a wide range of areas and able to work in a cross-disciplinary team. Applications are welcomed from a wide range of disciplines including engineering, computer science, healthcare professions and other backgrounds. A practical interest in the integration of digital healthcare data from both bespoke sensors and ubiquitous smart devices with specific computational infrastructure is needed. An upper second class degree at undergraduate level is required and previous experience in research is desirable.

Each project’s supervisory team will include one clinician from Sheffield Children’s Hospital and up to two academic members of the Insigneo Institute, University of Sheffield. Supervisors will be allocated to suit the specifics of the research and may change from those stated.

Entry Requirements:

Candidates must have a first or upper second class honours degree or significant research experience. A practical interest in the integration of digital healthcare data from both bespoke sensors and ubiquitous smart devices with specific computational infrastructure is needed.

The ideal student will have:

• Academic Background: Applicants should have a strong academic background in a relevant discipline such as engineering, computer science, mathematics, physics, healthcare, or another related field.
• Research Experience: Applicants should have prior research experience, ideally in a related area. This could include experience gained through previous research projects, internships, or work experience.
• Interdisciplinary Skills: The PhD program requires working in a highly interdisciplinary environment, so applicants should have strong interdisciplinary skills and be able to work well with people from different backgrounds and disciplines.
• Technical Skills: Applicants should have good technical skills, including knowledge of programming languages, software tools, and statistical analysis techniques. They should also have a good understanding of digital technologies and their potential applications in healthcare.
• Communication Skills: Applicants should have excellent communication skills, both written and verbal. They should be able to explain their research clearly and effectively to a range of audiences, including healthcare professionals, patients, and other stakeholders.
• Motivation and Enthusiasm: Applicants should be highly motivated and enthusiastic about the research area and have a strong interest in making a meaningful contribution to child health.
• Eligibility: Applicants should meet the eligibility requirements for PhD study at the University of Sheffield. This typically includes having a good undergraduate degree and meeting the English language proficiency requirements

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 in the respective box and select Department of Infection, Immunity & Cardiovascular Disease as the department.

Enquiries:

Pre-application and informal enquiries accompanied by a CV are encouraged to Sarah Black (Insigneo Administrative Manager) sarah.black@sheffield.ac.uk

Funding: 

Funding for these PhDs is provided by the NIHR Great Ormond Street Biomedical Research Centre and Sheffield Children’s NHS Foundation Trust as part of their Paediatric Excellence Initiative. The NIHR Great Ormond Street Hospital BRC (GOSH BRC) is a partnership between Great Ormond Street Hospital and the University College London (UCL) Great Ormond Street Institute of Child Health (ICH). Now it’s in its fourth 5-year term, as part of a wider national collaboration - a BRC National Paediatric Excellence Initiative has been set up between GOSH BRC and children’s hospitals in Birmingham, Sheffield and Liverpool. 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 discovery of new treatments for children with rare and complex conditions.

Funding Notes

Salary/stipend rate:

• The UKRI doctoral stipend for 2022/23 - £17,668 full time equivalent per annum
• Project expenses – up to £500 per annum
• Home student tuition fees will be covered. Overseas students will be required to cover the financial shortfall between home and overseas student fees.

Proposed start date: 1 October 2023

The Sheffield Children’s Hospital/Insigneo Institute for In Silico Medicine PhD Programme in Digital Health: Digital Twins

About the Project

Supervisor(s): 

Professor Jim Wild (representing a team of potential supervisors from Insigneo) and Professor Paul Dimitri (representing a team of potential supervisors from SCH)

Sheffield Children’s Hospital, the NIHR Children and Young People MedTech Cooperative and the Insigneo Institute for In Silico Medicine at the University of Sheffield are recruiting up to 4 PhD studentships in Paediatric Digital Healthcare Technology, this PhD is specifically looking at Digital Twins.

Successful applicants will work together in a pioneering cross-disciplinary programme alongside patients, families, clinicians, engineers, computer scientists and other experts to develop new digital platforms and technologies that can address unmet needs in child health. This research will focus on paediatric clinical care pathways and span the Insigneo research themes of Healthcare Data, Artificial Intelligence and Smart Devices and Sensors. It will develop the concepts of Digital Twins, Digital Wards, Digital Healthcare at Home and Advanced Healthcare Communication in paediatric real life healthcare settings with Sheffield Children’s Hospital and in collaboration with Great Ormond Street Hospital.

Each project will follow three stages.

Stage 1

Each project will work with clinicians, patients and families in a series of workshops to identify a specific clinical problem in disease areas such as respiratory disease, neurology, musculoskeletal disease and mental health that could be improved by capture and transfer of digital data from current or newly developed sensors and other technologies used by the patient and or their family at home and in daily life.

Stage 2

Projects will then work with academic teams of engineers and industrial partners to develop prototype technologies required to obtain the data identified in Stage 1 and the secure IT and telecommunication infrastructure required to present the data to the patient/family and the clinical team. Iterative co-design will optimise technology and interface design.

Stage 3

Once technologies and digital infrastructures are established, projects will work with patients/families and clinicians to design novel care pathways that use the data generated to; a) optimise frequency of remote or in-person clinical review b) alter treatment decisions c) create efficient healthcare delivery with minimal intrusion.

Successful completion will lead to functional data capture and exchange platforms and a proposed clinical pathway for each clinical problem and its technological solution. These will be at the point of readiness for follow on clinical studies testing their ability to improve outcomes such as patient/family satisfaction, patient-reported outcomes, reduction of hospital visits/admissions, and clinical outcomes compared with current standard-of-care.

Applicants must be highly motivated, adaptable, willing to learn skills from a wide range of areas and able to work in a cross-disciplinary team. Applications are welcomed from a wide range of disciplines including engineering, computer science, healthcare professions and other backgrounds. A practical interest in the integration of digital healthcare data from both bespoke sensors and ubiquitous smart devices with specific computational infrastructure is needed. An upper second class degree at undergraduate level is required and previous experience in research is desirable.

Each project’s supervisory team will include one clinician from Sheffield Children’s Hospital and up to two academic members of the Insigneo Institute, University of Sheffield. Supervisors will be allocated to suit the specifics of the research and may change from those stated.

Entry Requirements:

Candidates must have a first or upper second class honours degree or significant research experience. A practical interest in the integration of digital healthcare data from both bespoke sensors and ubiquitous smart devices with specific computational infrastructure is needed.

The ideal student will have:

• Academic Background: Applicants should have a strong academic background in a relevant discipline such as engineering, computer science, mathematics, physics, healthcare, or another related field.
• Research Experience: Applicants should have prior research experience, ideally in a related area. This could include experience gained through previous research projects, internships, or work experience.
• Interdisciplinary Skills: The PhD program requires working in a highly interdisciplinary environment, so applicants should have strong interdisciplinary skills and be able to work well with people from different backgrounds and disciplines.
• Technical Skills: Applicants should have good technical skills, including knowledge of programming languages, software tools, and statistical analysis techniques. They should also have a good understanding of digital technologies and their potential applications in healthcare.
• Communication Skills: Applicants should have excellent communication skills, both written and verbal. They should be able to explain their research clearly and effectively to a range of audiences, including healthcare professionals, patients, and other stakeholders.
• Motivation and Enthusiasm: Applicants should be highly motivated and enthusiastic about the research area and have a strong interest in making a meaningful contribution to child health.
• Eligibility: Applicants should meet the eligibility requirements for PhD study at the University of Sheffield. This typically includes having a good undergraduate degree and meeting the English language proficiency requirements

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 in the respective box and select Department of Infection, Immunity & Cardiovascular Disease as the department.

Enquiries:

Pre-application and informal enquiries accompanied by a CV are encouraged to Sarah Black (Insigneo Administrative Manager) sarah.black@sheffield.ac.uk

Funding: 

Funding for these PhDs is provided by the NIHR Great Ormond Street Biomedical Research Centre and Sheffield Children’s NHS Foundation Trust as part of their Paediatric Excellence Initiative. The NIHR Great Ormond Street Hospital BRC (GOSH BRC) is a partnership between Great Ormond Street Hospital and the University College London (UCL) Great Ormond Street Institute of Child Health (ICH). Now it’s in its fourth 5-year term, as part of a wider national collaboration - a BRC National Paediatric Excellence Initiative has been set up between GOSH BRC and children’s hospitals in Birmingham, Sheffield and Liverpool. 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 discovery of new treatments for children with rare and complex conditions.

Funding Notes

Salary/stipend rate:

• The UKRI doctoral stipend for 2022/23 - £17,668 full time equivalent per annum
• Project expenses – up to £500 per annum
• Home student tuition fees will be covered. Overseas students will be required to cover the financial shortfall between home and overseas student fees.

Proposed start date: 1 October 2023

EPSRC Doctoral Training Partnership: A computational biomechanical model to optimise personalised treatments for spine metastases

About the Project

The management of patients with vertebral metastases is critical, due to the challenging assessment of vertebral stability and the need to decide whether the patient needs an invasive intervention to fix the spine.  Subject Specific Finite Element (SS-FE) models based on clinical images of the patient can accurately predict the vertebral fracture risk but have not been optimised nor validated for identifying the best treatment for metastatic vertebrae. This is due to computational modelling challenges and the lack of experimental assessment of the biomechanical properties of healthy, metastatic and treated spine functional units (SFUs) that can be used to validate the outcomes of the models, a fundamental step before their clinical application. 

Recently Dr Dall’Ara’s team has developed a unique experimental pipeline for the biomechanical assessment of the SFUs under compression.  This pipeline has been used to study the biomechanical properties of a large number of vertebrae with and without metastases and will soon include also experiments on treated SFUs. Therefore, for the first time we can use this data to validate the computational models and identify the best personalised treatments for oncologic patients with metastatic lesions in the spine. 

The hypothesis of this study is that SS-FE models can be used to identify the best treatment for reducing the negative effects of vertebral metastases on the bone strength. The study will reach the following three objectives:

1) Development of a pipeline to create subject-specific finite element (SS-FE) models of SFUs for predicting the bone compressive strength in healthy, metastatic and treated vertebrae;

2) Validation of the outputs of the SS-FE models of the SFU against experimental measurements;

3) Application of the SS-FE models to identify the best personalised treatments for a small cohort of oncologic patients suffering from spine metastases.

The student will learn how to create computational models based on medical images, validate the outputs of the models with state of the art biomechanical data, and apply the models to solve an important clinical problem.

Entry Requirements:

Candidates must have a first or upper second class honours degree or significant research experience. 

How to apply:

Please complete a University Postgraduate Research Application form available here: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying

Please clearly state the prospective main supervisor in the respective box and select ‘Oncology and Metabolism’ as the department.

Enquiries:

Interested candidates should in the first instance contact Dr Dall'Ara e.dallara@sheffield.ac.uk

Proposed start date - October 2023

Funding Notes

This EPSRC Doctoral Training Paternship Scholarship covers tuition fees and stipend at UKRI rate for 3.5 years. A Research Training Support Grant is also included.