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- Tasks: Develop a mathematical model to enhance medical process reliability using AI and system modelling.
- Company: Join the University of Nottingham, a leader in health sciences research and innovation.
- Benefits: Gain hands-on experience in healthcare modelling and cutting-edge computer vision techniques.
- Why this job: Make a real impact on patient safety while working with advanced technology in a supportive environment.
- Qualifications: Open to UK students with a 1st class degree in engineering, maths, or related fields.
- Other info: Applications are encouraged early as the position is open until filled.
The predicted salary is between 30000 - 50000 £ per year.
PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques
Join to apply for the PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques role at University of Nottingham
PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques
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Join to apply for the PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques role at University of Nottingham
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Area
Health Sciences Research & Teaching
Location
UK Other
Closing Date
Open Until Filled
Reference
MEDINTERN
PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques
Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group)
Aim: Develop a mathematical model for analysing reliability and efficiency of medical processes
Background
Adverse events and preventable failures in healthcare services represent a key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which influences process reliability, efficiency of usage of hospital resources and risk to staff and patient safety. Hence, having a model that integrates these various aspects of procedure is essential to result in a more accurate analysis of optimizing the service performance. Computer vision approaches such as ones for object identification and action recognition can help to automatically identify deviations in both technical and potentially non-technical skills of medical staff, such as poor team dynamics, problems with communication and a lack of leadership. This automated obtained data can then be fed into the models that are used to evaluate a range of deviations from guidelines including their interactions and effects on procedure outcomes and used to support operational and strategic decisions. This approach is expected to provide a more convenient and efficient way of healthcare service performance data acquisition and analysis in the future. However, undoubtedly, the usage of such approaches can only become successful if patients are placed in the heart of technology usage, which is designed with patients’ perspective in mind.
Proposed project
This project would investigate commonly observed deviations in healthcare service and opportunities for identification of such deviations using computer vision approaches. It will demonstrate how deviation data can be used in computer-based simulation models, which are used to evaluate effects of deviations and to support decisions. It will focus on investigating how deviation data can be used in real time decision-making process, how accepting patients and staff are for such technologies and what integral role they should play in evaluating and ensuring an uptake of such technologies. The proposed method will be potentially applied to processes carried out in an operating theatre.
Benefits of joining this project:
This project will give an opportunity for the student to explore the area of healthcare process modelling with a holistic perspective considering various elements in the process. The integration of computer vision techniques in this project will also enhance the value of this work. The students will not only gain an experience and insight on healthcare service characteristics but also a skill in one of the most attractive areas of technology nowadays.
Summary: Open to UK students only. Look for funding sources at https://www.nottingham.ac.uk/pgstudy/funding/postgraduate-funding.aspx
Entry Requirements: Starting October 2025, we require an enthusiastic graduate with a 1st class degree in engineering, maths or a relevant discipline, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered).
To apply visit: http://www.nottingham.ac.uk/pgstudy/apply/apply-online.aspx
For any enquiries about the project and the funding please email Rasa Remenyte-Prescott ( r.remenyte-prescott@nottingham.ac.uk )
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
This studentship is open until filled. Early application is strongly encouraged.
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PhD studentship: Improving reliability of medical processes using system modelling and Artifici[...] employer: University Of Nottingham
Contact Detail:
University Of Nottingham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land PhD studentship: Improving reliability of medical processes using system modelling and Artifici[...]
✨Tip Number 1
Familiarise yourself with the latest advancements in system modelling and artificial intelligence, particularly in healthcare. This will not only help you understand the project better but also allow you to engage in meaningful discussions during interviews.
✨Tip Number 2
Connect with current or former PhD students in similar fields at the University of Nottingham. They can provide valuable insights into the application process and what to expect from the programme.
✨Tip Number 3
Attend relevant workshops or seminars related to healthcare technology and AI. Networking at these events can lead to connections that may support your application and provide recommendations.
✨Tip Number 4
Prepare to discuss how your background in engineering or maths can contribute to the project’s goals. Think about specific examples where you've applied your skills in real-world scenarios, especially in healthcare settings.
We think you need these skills to ace PhD studentship: Improving reliability of medical processes using system modelling and Artifici[...]
Some tips for your application 🫡
Understand the Project: Before applying, make sure to thoroughly read the project description. Understand the aims and objectives of the PhD studentship, especially how it relates to improving medical processes using system modelling and AI techniques.
Tailor Your CV: Craft your CV to highlight relevant experience in engineering, maths, or related disciplines. Emphasise any projects or coursework that align with healthcare process modelling or computer vision techniques.
Write a Strong Personal Statement: In your personal statement, express your enthusiasm for the project and how your background makes you a suitable candidate. Discuss your interest in healthcare technology and any relevant skills or experiences that demonstrate your capability.
Follow Application Instructions: Ensure you follow the application instructions provided on the University of Nottingham's website. Pay attention to details such as document formats, submission deadlines, and any specific requirements mentioned in the job description.
How to prepare for a job interview at University Of Nottingham
✨Understand the Project Scope
Familiarise yourself with the details of the PhD project, especially the focus on system modelling and AI techniques in healthcare. Be prepared to discuss how your background aligns with these areas and how you can contribute to improving medical processes.
✨Showcase Relevant Skills
Highlight any experience you have with mathematical modelling, computer vision, or healthcare processes. Be ready to provide examples of past projects or coursework that demonstrate your proficiency in these skills.
✨Prepare Questions
Think of insightful questions to ask during the interview. This could include inquiries about the research group's current projects, the integration of patient perspectives in technology, or potential challenges in the field. It shows your genuine interest and engagement.
✨Express Enthusiasm for Research
Convey your passion for healthcare improvement and research. Discuss why this PhD studentship excites you and how it fits into your long-term career goals. Enthusiasm can make a strong impression on the interviewers.
