PhD scholarship in Human-XAI Collaboration for Improved Fetal Ultrasound Imaging - DTU Compute

You will develop explainable AI algorithms whose target is to support non-specialist clinicians in obtaining high quality fetal ultrasound images, while simultaneously improving their skill. The position requires both a practical skill set in developing robust deep learning algorithms and user friendly interfaces, but also a passion for collaborating with clinical users to create algorithms that are designed to accommodate their learning.
Are you our new colleague? We are seeking a PhD student in Explainable AI (XAI) and Human-Computer Collaboration who is passionate about creating and validating XAI algorithms based on their actual utility to its users. This project is dedicated to developing and validating XAI algorithms designed to support clinicians in obtaining higher quality fetal ultrasound images, while simultaneously improving their image acquisition skills.

In addition to creating and implementing XAI algorithms, your research will also include developing quantitative learning analytics that quantify the skill of clinicians based on their results and behavior while performing fetal ultrasound scans.

You will be part of an interdisciplinary team including clinicians, medical education experts, and technical researchers, and your job will include both the technical development of XAI algorithms and user interfaces, but also participation in testing XAI algorithms with real clinical users.

This project addresses a crucial yet often overseen aspect of XAI: How to validate its effect, and most importantly, its utility, for different target groups of users.

Responsibilities and qualifications
Your main tasks will be to implement a range of XAI feedback forms as well as learning analytics, and to collaborate closely with clinicians and medical education researchers in assessing how different types of XAI feedback affects different types of clinicians.

The development of XAI algorithms will build on existing work from our team, but will also be applied to ultrasound simulators, where clinicians can practice with no risk of patient harm. As such, part of your work will also be dedicated to transferring models between real images and fetal ultrasound simulator images.

Your primary tasks will be to:

• Develop quantitative learning analytics that assess the skill of clinicians based on how they carry out a fetal ultrasound screening scan
• Implement a range of XAI algorithms to be tested with different groups of users, along with user interfaces
• Collaboration with clinicians and medical education experts to validate the effect of different types of XAI feedback for different groups of clinicians
• Writing and presenting scientific papers in top conferences and journals
• Working as a teaching assistant in four 5 ECTS modules

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 assessment will be made by Aasa Feragen and Anders Nymark Christensen from DTU Compute and Martin Tolsgaard from CAMES Rigshospitalet.

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. Starting date is 1 April 2025 (or according to mutual agreement). 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 Aasa Feragen, [email protected].

You can read more about DTU Compute at www.compute.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 15 January 2025 (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, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.

DTU Compute
DTU Compute is a unique and internationally recognized academic department with 385 employees and 11 research sections spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard – producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science. At DTU Compute we believe in a diverse workplace with a flexible work-life balance.

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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