Phd Research Fellow in Tecnology: Computer Science

University of South-Eastern Norway
Raveien 215, 3184 Borre
Om jobben
Lagre favoritt
Stillingstittel
**PhD Research Fellow in Technology**: Computer science
Type ansettelse
Åremål, heltid 100%
Antall stillinger
1
Arbeidsspråk
Engelsk
Søk senest mandag 31. august
About the position
Are you interested in Applied Artificial Intelligence, Education, and Medicine, and want to engage in research with skilled colleagues who share your interests? Maybe you can become our new colleague?
You will be affiliated with the PhD program in Technology at the Faculty of Technology, Natural Sciences and Maritime Sciences and formally employed at det USN School of business.
The PhD research fellowship is for a fixed term of three years with organized research training and is available from (or earlier if possible).
It is a condition that the person who accepts the position applies for and is granted admission to the doctoral programme in Technology within three months of starting in the position. The doctoral program includes relevant courses corresponding to approximately six months of study (30 ETCS), a thesis based on independent research, active participation in national and international research environments, relevant research dissemination, a trial lecture and public defense of the thesis. Read more about organised research training at USN on our website.
Your personnel manager will be Bjørn Hansen, the Head of Department of Business, History and Social Sciences, and your main supervisor will be Associate professor Katarina Mangaroska. The place of work will be at campus Vestfold.
About the doctoral project
The BRAIGED project aims to develop an explainable AI-driven educational diagnostic assistant enabling new research on how AI technologies create novel prerequisites, opportunities and challenges for learning, decision-making, and clinical reasoning in medicine. The project aims to move explainability beyond a purely technical feature and toward an interactive educational process that supports metacognitive reasoning, student agency, and responsible use of AI. The project will generate new knowledge and practical tools for implementing context-appropriate explainable AI solutions in medical education.
A central use case is kidney disease (e.g., CKD) and clinical reasoning using renal scintigraphy imaging alongside tabular and textual clinical data. The project integrates experiential learning models and simulation-based learning scenarios, grounded in the paradoxical inquiry framework, to recognize and embrace contradictions inherent in AI-driven medical training.
During the doctoral project, we expect you to
Complete the doctoral program and obtain the doctoral degree within the employment period
Conduct high-quality research within the framework of the BRAIGED project
Develop a theoretically grounded and methodologically rigorous PhD project related to responsible, explainable and governable AI in healthcare and medical education
Contribute to scholarly publications in high-quality international journals and conferences
Participate actively in the research group’s activities, including seminars, workshops, project meetings and collaborative research discussions
Participate in relevant courses offered through the doctoral program
Contribute to interdisciplinary collaboration with researchers, healthcare professionals, educators, students and other project partners involved in BRAIGED
Contribute to data collection and analysis (qualitative and quantitative): interviews, focus groups, surveys, usability studies and learning-scenario data
Develop and evaluate machine learning pipelines (including preprocessing, segmentation/feature extraction, model training and validation)
Design and test explainability methods
Support the co-design and iterative prototyping of AI-driven educational diagnostic assistant tool
Be prepared for changes in your work tasks after appointment
**Qualifications**:
Master’s degree (120 ECTS credits) (or equivalent qualifications) within Computer Science, AI, Data Science, Machine Learning; Biomedical Engineering, Medical Informatics; or a closely related discipline
Documented knowledge of relevant methodologies, both quantitative and/or qualitative, at master’s level
Excellent written and oral English language skills (See “Requirements for proficiency in English)
Meet the formal requirements for admission to USN’s doctoral programmes and Faculty for Technology, Natural Sciences and Maritime’s doctoral programme in Technology no later than three months after starting in the position
Personal qualities
In order to be able to complete a doctoral degree within the deadline, you need to be able to:
Demonstrate motivation and potential for research in the field
Work independently, but also participate in teamwork
Work in a structured way, set goals, and make plans to achieve them
Present and discuss your research with other academics
Get involved an