PhD Candidate in Explainable AI (xAI) for Capsule Endoscopy

for automated diagnostic decision systems to enhance the explainability and actionability of their predictions for doctors. The candidate will also evaluate the generated explanations with medical doctors to assess their relevance, usefulness, and importance in clinical settings. Key responsibilities

• Complete the doctoral education until obtaining a doctorate
• Carry out research of good quality within the framework described above
• Academic publications and popular science dissemination
• Participate in the Colourlab research group
• Participate in the network's joint research and training activities, both online and in person across the CAPTURE partner institutions and contribute to CAPTURE project deliverables in accordance with the Description of Action and the project's governance procedures.
• Participate in international activities such as conferences and/or research stays at foreign educational institutions. Particularly, secondments of a few months' duration are foreseen to Robert Gordon University, UK and Technical University of Darmstadt, Germany.
• Close collaboration with hospitals for assessing methods developed in PhD project

Be prepared for changes to your work duties after employment.

• You must have experience with computer vision and machine learning.
• You must have excellent programming skills in Python with exposure to popular deep learning libraries like PyTorch or Tensorflow.
• At the date of recruitment, you must NOT have been awarded a doctoral degree. Researchers who have successfully defended their doctoral thesis but have not yet formally been awarded the degree are also not eligible.
• You must meet the requirements for admission to the faculty's Doctoral Programme in computer science , see Section 6-1 of the PhD regulations for more information.
• You must have a relevant master's degree in computer science, electrical engineering or equivalent. Your degree must include a major independent project (minimum 30 ECTS) equivalent to a master's thesis.
• Master students can apply, but the master's degree must be obtained and documented before starting the position.
• You must have a strong and relevant academic background from your previous studies and have an average grade from your master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker academic background, you may be considered if you can document that you are exceptionally suited for a PhD education, for example through relevant work experience and/or peer-reviewed academic works.
• Excellent oral and written communication skills in English.
• You must comply with the MSCA mobility rule: you must not have resided or carried out your main activity (work, studies, etc.) in the country of the recruiting organisation for more than 12 months in the 36 months immediately before recruitment (short stays such as holidays are not taken into account).

The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position.

Preference may be given to candidates with:

• Experience with computer vision, medical image processing, self-supervised learning or learning in low-data regimes.
• Experience with statistical signal processing and pattern recognition will be counted positive.
• Experience with pretrained representation models, transfer learning and xAI.
• Knowledge of robustness analysis in computer vision applications.
• Knowledge of explainable AI, uncertainty estimation, calibration, out-of-distribution detection, adversarial robustness, or causal analysis.
• Experience with causal inference, counterfactual explanations, or uncertainty quantification in deep learning
• Evidence of scientific writing, publications, a strong master's thesis, research software, or relevant open-source contributions.
• Excellent analytical and communication skills.
• Ability to work in an international and interdisciplinary environment.

To complete a doctoral degree (PhD), it is important that you are able to:

• Show strong motivation for research and a willingness to engage deeply with challenging scientific questions.
• Work in a structured way, set goals and make plans to achieve them.
• Present and discuss your research with other professionals.
• Get involved and contribute constructively with feedback.
• Work constructively under pressure or in the face of adversity.
• Show curiosity and a strong motivation for the subject.
• Analyze data, assess different perspectives and draw well-founded conclusions.
• Be flexible and open to adjusting the plan for the project as needed.
• Communicate, present, and collaborate effectively, including explaining technical ideas clearly and presenting research results to interdisciplinary audiences and project partners.

Emphasis will be placed on personal qualities.

• An exciting job with an important mission in society
• Developing tasks in a strong and international professional environment
• Career guidance and follow-up during the PhD period
• Open and inclusive working environment with committed colleagues
• Favorable terms as a member of the Norwegian Public Service Pension Fund (SPK)
• Free Norwegian language training at a basic level (A2)
• As an employee in Norway, the successful candidate will normally be a member of the Norwegian National Insurance Scheme, which provides access to public healthcare and social security benefits in accordance with applicable legislation and regulations.

As a PhD Candidate at NTNU, you will have access to employee benefits .

the application will only be assessed on the basis of the information we have received by the application deadline. Therefore, make sure that your application clearly shows how your skills and experience meet the criteria described above. The application and all attachments must be sent electronically via Jobbnorge.no. If you are invited to an interview, you must bring certified copies of certificates and diplomas upon request. Incomplete applications will not be prioritised. The application must include:

• Transcripts and diplomas for Bachelor's and Master's degrees
• CV
• Copy of master's thesis. If you have recently submitted your master's thesis, you can attach a draft of the thesis. Documentation of a completed master's degree must be presented before taking up the position.
• Project outline containing proposals for an overall description of research questions, theoretical perspectives, methodological design for the project and progress plan (maximum 1500 words/4 pages).
• Short letter of motivation (400 words/1 page).
• Possibly publications etc. other relevant research work.
• Possibly certificates.
• Names and contact information of at least two relevant referees.

If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both Bachelor's and Master's education, in addition to other higher education. If your institution uses "diploma supplement" (normal for most European institutions), you must attach this. A description of the documentation required can also be found here . If you already have a statement from Norwegian Directorate for Higher Education and Skills (HK-dir) , please attach this as well. Joint work will be considered. If it is difficult to identify your contribution to joint work, you must attach a brief description of your participation. When assessing the best qualified, we emphasize necessary qualifications such as education, experience and personal suitability. Motivation for the position, ambitions, and potential for research will also count when assessing the candidates.

NTNU recognizes a wide range of academic contributions and has committed itself to The San Francisco Declaration on Research Assessment and CoARA (responsible assessment of research and recognition of a greater breadth of academic contributions in accordance with NTNU's social mission).