At a Glance
- Tasks: Explore AI-driven medical imaging fusion for advanced diagnostic tools.
- Company: University of Southampton, a leader in engineering and physical sciences.
- Benefits: Competitive funding for tuition and living stipend, plus excellent work-life balance.
- Other info: Join a diverse team committed to equality and sustainability.
- Why this job: Make a real impact in healthcare with cutting-edge technology and research.
- Qualifications: Strong undergraduate degree (UK 2:1 or equivalent) required.
The predicted salary is between 18000 - 25000 £ per year.
Three dimensional images of the foot taken under loading conditions can provide a valuable clinical tool for the assessment of bone alignment related complaints. However, as these images have to be taken whilst a person is standing, specialised scanners are required to collect the image data. With limited availability of the required specialised equipment, most diagnostic decisions still have to be made based on traditional images, such as weightbearing two dimensional projective radiographic images or non-weightbearing three-dimensional X-ray computed tomography (CT) images, which can be generated with equipment readily available in most clinical settings.
This PhD project will explore the feasibility of combining information from several weightbearing two-dimensional projective X-ray images with non-weightbearing three-dimensional tomographic data to extract the clinically salient diagnostic information. Working closely with orthopaedic surgeons, the project is anticipated to use both simulated as well as real X-ray image data in order to develop advanced image processing and computer vision algorithms to combine information from the two modalities.
Utilising the latest advances in machine learning, the project aims to overcome two fundamental challenges:
- The identification of the unknown alignment of the two-dimensional projective X-ray images relative to the X-ray imaging system.
- The identification of key anatomical landmarks in each of the images that will allow for the precise alignment of the different anatomical structures in each of the imaging conditions.
Potential funding to support this position will be available to the strongest candidates through the Faculty of Engineering and Physical Sciences graduate school studentship programme, which are awarded on a competitive basis.
If you wish to discuss any details of the project informally, please contact Professor Thomas Blumensath, µ-VIS X-ray imaging centre, Email: Thomas.blumensath@soton.ac.uk, Tel: +44 (0) 2380 59 3224.
Entry Requirements
A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).
Closing Date: 31 August 2024. Applications will be considered in the order that they are received, the position will be considered filled when a suitable candidate has been identified.
Funding: Funding for tuition fees and a living stipend are available on a competitive basis. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
How To Apply
Apply online: Search for a Postgraduate Programme of Study (soton.ac.uk). Select programme type (Research), 2024/25, Faculty of Engineering and Physical Sciences, next page select “PhD Engineering & Environment (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Thomas Blumensath.
Applications should include:
- Curriculum Vitae
- Two reference letters
- Degree Transcripts/Certificates to date
For further information please contact: feps-pgr-apply@soton.ac.uk
The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
PhD Studentship: AI-Driven Medical Imaging Fusion in Southampton employer: University of Southampton
The University of Southampton offers an exceptional environment for PhD candidates, particularly in the field of AI-driven medical imaging. With a strong commitment to equality, diversity, and inclusivity, the university fosters a supportive work culture that prioritises employee well-being through generous benefits such as maternity policies and onsite childcare. Additionally, the opportunity to collaborate with leading experts and access cutting-edge resources enhances professional growth and development, making it an ideal place for aspiring researchers.
StudySmarter Expert Advice🤫
We think this is how you could land PhD Studentship: AI-Driven Medical Imaging Fusion in Southampton
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of AI and medical imaging. Attend relevant conferences or webinars, and don’t be shy about introducing yourself. You never know who might have a lead on your dream PhD position!
✨Tip Number 2
Get in touch with Professor Thomas Blumensath directly. A quick email or call can show your genuine interest in the project. Plus, it’s a great way to ask any burning questions you might have about the studentship.
✨Tip Number 3
Make sure your CV shines! Tailor it to highlight your skills in image processing, machine learning, and any relevant research experience. We want to see how you can contribute to this exciting project!
✨Tip Number 4
Apply early through our website! Remember, applications are considered on a rolling basis, so the sooner you get your application in, the better your chances. Don’t miss out on this fantastic opportunity!
We think you need these skills to ace PhD Studentship: AI-Driven Medical Imaging Fusion in Southampton
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience and skills that align with the PhD project. We want to see how your background fits into the world of AI-driven medical imaging, so don’t hold back on showcasing your strengths!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about this project and how your expertise can contribute. We love seeing enthusiasm and a clear understanding of the research area.
Gather Strong References:Choose referees who know your work well and can speak to your abilities in research or related fields. A solid reference can make all the difference, so give them a heads-up about the specifics of the PhD project!
Apply Early!:Since applications are considered on a rolling basis, we recommend getting your application in as soon as possible. The sooner you apply, the better your chances of securing funding and being considered for the position!
How to prepare for a job interview at University of Southampton
✨Know Your Stuff
Make sure you’re well-versed in the latest advancements in AI and medical imaging. Brush up on relevant algorithms and techniques, especially those related to image processing and computer vision. Being able to discuss these topics confidently will show your passion and expertise.
✨Connect with the Project
Familiarise yourself with the specifics of the PhD project. Understand the challenges mentioned, like aligning two-dimensional and three-dimensional images. Prepare to discuss how your background and skills can contribute to overcoming these challenges.
✨Ask Insightful Questions
Prepare thoughtful questions for Professor Blumensath or the interview panel. This could be about the methodologies they plan to use or the potential impact of the research. It shows your genuine interest and helps you gauge if the project aligns with your goals.
✨Showcase Your Team Spirit
Since this project involves collaboration with orthopaedic surgeons, highlight any previous teamwork experiences. Discuss how you’ve successfully worked in interdisciplinary teams before, as this will demonstrate your ability to communicate and collaborate effectively.
