PhD scholarship in A Digitalization Approach for Wall Shear Stress Estimation

Are you passionate about revolutionizing medical imaging with cutting-edge machine learning? Do you aspire to contribute to groundbreaking research that significantly enhances clinical workflows and patient outcomes?
Are you passionate about revolutionizing medical imaging with cutting-edge machine learning? Do you aspire to contribute to groundbreaking research that significantly enhances clinical workflows and patient outcomes? The Technical University of Denmark (DTU) is seeking ambitious candidates for a PhD position focused on developing an innovative high-frame-rate ultrasound-based wall shear stress (WSS) estimation framework. This project aims to transform stroke prevention by integrating state-of-the-art machine learning techniques with advanced ultrasound imaging.

Stroke, a leading cause of death worldwide, often results from the rupture of fatty deposits called plaques in aging blood vessels, such as the carotid artery. These ruptured plaques release blood clots that travel to the brain, blocking blood vessels and causing severe brain function impairment. Wall shear stress (WSS) plays a critical role in plaque formation and rupture, influencing how blood flow interacts with vessel walls. With an aging population, Europe is projected to experience 1.5 million stroke cases annually by 2025. There is an urgent need for better tools to assess plaque development and predict rupture risk, as current methods, like MRI, are costly and cannot capture WSS dynamics. Ultrasound offers a real-time, cost-effective solution for mapping these dynamics.

This PhD project aims to develop a novel WSS estimation framework by integrating high-frame-rate ultrasound with advanced deep learning algorithms, enabling accurate measurements. The project will address key research challenges, including robust vessel wall segmentation and flow estimation using physics-informed neural networks.

What You Can Achieve by Joining DTU:

• Cutting-Edge Research Experience: Engage in pioneering research at the intersection of medical imaging and machine learning, contributing to advancements in stroke prevention and clinical workflows
• Advanced Skill Development: Develop and refine your expertise in high-frame-rate ultrasound imaging, machine learning, and AI-based image analysis, positioning yourself at the forefront of technological innovation
• Professional Growth: Benefit from mentorship by leading experts in the field, access state-of-the-art facilities, and participate in professional development opportunities through courses, workshops, and conferences

By joining DTU, you will be part of a transformative journey that advances your career and contributes to significant improvements in medical science and patient care.

Responsibilities and qualifications
We are seeking a motivated candidate with experience in deep learning for image processing and analysis. Your main focus will be to enhance the department's expertise in ultrasound flow imaging and deep learning, contributing to the development of innovative diagnostic tools. You will collaborate with colleagues, as well as academic and industrial partners both in Denmark and internationally.

Your primary tasks will be to:

• Conduct research in the field of high-frame-rate ultrasound imaging and machine learning
• Develop and implement machine learning models for vessel wall segmentation and WSS estimation
• Test and refine the proposed techniques through in-vitro flow phantom studies
• Collaborate with clinical partners at hospitals for data collection and clinical validation
• Publish research findings in international peer-reviewed journals and present at conferences
• Teach and supervise BSc and MSc student projects

Key Professional competencies Needed:

• Technical Expertise: Strong background in applied mathematics, computer science, biomedical engineering, or related fields; proficiency in image processing, computer vision, and machine learning techniques
• Programming Skills: Advanced programming skills in languages such as Python, MATLAB, or similar, with experience in relevant deep learning packages
• Medical Imaging Knowledge: Familiarity with medical imaging modalities, particularly ultrasound imaging; experience in high-frame-rate ultrasound imaging is highly desirable
• Analytical Skills: Ability to analyze complex and large datasets, develop new methodologies, and validate the accuracy of the developed models

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

Assessment
The applicants will be assessed by Associate Prof. Yiu and Prof. Dahl, and the scholarship for the PhD degree is subject to academic approval. The candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

The starting date is December 1st, 2024 (or according to mutual agreement), and the position is a full-time position.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Associate Professor Yat Shun Yiu (yshyi@dtu.dk) and Professor Anders Bjorholm Dahl (adba@dtu.dk).

You can read more about DTU Health Tech at www.healthtech.dtu.dk, DTU Compute at www.compute.dtu.dk, and Centre for Fast Ultrasound at cfu.dtu.dk.

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

Application procedure
Your complete online application must be submitted no later than 4 September 2024 (23:59 Danish time).

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• A letter motivating the application (cover letter)
• Curriculum vitae
• Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

The position will be at DTU Health Tech in the Section for Ultrasound and Biomechanics and co-supervised by DTU Compute in the Section for Visual Computing.

The Section for Ultrasound and Biomechanics is part of the Department of Health Technology (DTU Health Tech). DTU Health Tech aspires to improve good health and quality of life through technology for better prediction, prevention, early diagnosis, and treatment. DTU Health Tech strives to drive research and innovation towards the translation of the next generation healthcare solution in close collaboration with clinicians and basic researchers, and industry for the benefit of people and a sustainable society.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.

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