PhD Research Fellow in AI for Rehabilitation and Motor Learning
Deadline: 16.07.2026
Publisert
The University of Oslo is Norway’s oldest and highest rated institution of research and education with 26 500 students and 7 200 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society.
The University of Oslo (UiO) is expanding the activity at Campus Kjeller to strengthen our education, research, and innovation in technology for a sustainable future. UiO is a well-ranked research university where the Department of Technology Systems at Kjeller (ITS) is focused on applied research in sustainable energy, autonomous systems, space, and security. At Kjeller, ITS is co-located with the Norwegian Defense Research Establishment (FFI) and the Institute for Energy Technology (IFE), which both offer rich opportunities for collaboration. ITS also has a range of interdisciplinary research collaborations that include the UiO Blindern Campus and Oslo Science City, as well as many other national and international institutions and industries.
ITS offers several master level programmes, alone and jointly with other departments: Renewable energy systems, Cybernetics and autonomous systems, Robotics and intelligent systems, and Information security. ITS also hosts the Centre for Space Sensors and Systems (CENSSS), which incorporates operation of an instrument on the NASA Perseverance rover on Mars. A new master program in Space systems is in the planning stage. The department currently has 9 permanent scientific staff, approximately 35 adjunct staff from the research institutes at Kjeller and from industry, as well as about 20 PhD candidates. This position is part of an ongoing expansion of the UiO activity at Campus Kjeller. Campus Kjeller is located 20 km northeast of Oslo, between the city center and Oslo Airport. It is a 20 minutes commute with public transportation from Oslo city center to the campus.
About the position
We invite applications for position as PhD Research Fellow in Adaptive AI Environments for Biofeedback and Motor Learning available at Department of Technology Systems (ITS), University of Oslo.
Expected start date 01.10.2026 (flexible).
The fellowship period is three years.
A fourth year may be considered and it will involve 25 % of other career-promoting work. Other career-promoting work may consist of teaching, supervision, and/or research assistance. This is dependent upon the qualification of the applicant and the current needs of the department.
No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.
Place of work is Department of Technology Systems (ITS), at Kjeller, near Oslo.
Job description
The position is part of MishMash Centre for AI and Creativity, which is a Norwegian AI centre funded by the Research Council of Norway (2025-2030). It comprises more than 200 faculty members from many higher education institutions in Norway, in collaboration with numerous public and private sector partners. The primary objective of MishMash is to create, explore, and reflect on AI for, through, and in creative practices. MishMash researchers will investigate AI's impact on creative processes, develop innovative CoCreative AI systems and educational strategies, and address AI's ethical, cultural, legal, and societal implications in creative domains. See mishmash.no for more information.
How can an adaptive AI environment support a person's rehabilitation journey and help them achieve better, more durable motor control? MishMash Work Package 3 addresses the creative use of AI for health and well-being, examining how AI-generated content and AI-supported therapeutic practices can improve physical and mental well-being, while prioritizing ethical practices around consent, equity, and responsible therapeutic use.
This position investigates the design of adaptive, AI-driven interactive environments (serious games and biofeedback systems) that respond in real time to a user's physiological signals (such as muscle activity, movement, or cardiac signals), in order to support motor learning, rehabilitation, and therapeutic engagement. Because these environments must balance goal-directed adaptation with user agency and transparency, the project also connects to to MishMash WP1 on AI for artistic performances RQ1.1-1.2 and MishMash WP7 on human-centric AI for creative problem-solving. Building on recent work in Context-Informed Incremental Learning (CIIL), where controller and user co-adapt inside interactive environments without traditional calibration, the project addresses three central research questions:
First, how should the environment itself be designed to act as an effective teacher? This includes procedurally generating challenges that expose the user to meaningful variability, adapting difficulty and content in response to their physiological state, and structuring curricula that foster durable skill acquisition rather than narrow task performance.
Second, how do we ensure that skills acquired inside the adaptive environment transfer to real-world use? Improvements within a game mean little if they do not carry over into everyday function or clinical benefit. Designing, measuring, and promoting this transfer is a core objective of the project.
Third, how do we detect and prevent undesired adaptations, particularly compensatory movement patterns? When an AI-driven environment rewards task success without monitoring how the task is accomplished, users (and especially users in clinical populations) may learn motor strategies that achieve short-term rewards but reinforce harmful patterns. Multimodal sensing and AI-based detection of such patterns, integrated into the environment's reward and feedback structure, is a central methodological challenge.
The project will involve both healthy participants and clinical populations, in collaboration with Norwegian rehabilitation partners. The exact emphasis among the three questions, and the balance of methodological and applied work, will be shaped by the candidate’s interests and expertise within this scope.
The project is supervised by Associate Professor Ulysse Côté-Allard at the Department of Technology Systems, University of Oslo, whose research focuses on the development of machine learning algorithms, particularly transfer and adaptive learning, for multimodal wearable biosensing and its translation to rehabilitation and digital health applications. It is co-supervised by Professor Erik Scheme at the Institute of Biomedical Engineering, University of New Brunswick (Canada), whose group has long been at the forefront of myoelectric control, prosthetics research, and pattern recognition for clinical human-machine interfaces. A research stay at UNB is anticipated as part of the position.
The appointed candidate is expected to collaborate across the MishMash network and participate in all relevant MishMash activities.
What skills are important in this role?
The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.
Required qualifications:
Applicants must hold a Master's degree or equivalent in informatics, computer science, biomedical engineering, electrical engineering, human-computer interaction, or other relevant fields. The applicant is required to document that the degree corresponds to the profile of the post.
Grade average of B or better (or equivalent) for both the programme as a whole and the Master's thesis.
Strong programming skills (Python preferred) and foundations in machine learning.
Interest in adaptive interactive systems, biofeedback, or health and well-being applications.
The candidate's research proposal must be closely connected to the call and the research described in MishMash WP3.
Excellent skills in written and oral English.
Candidates who already hold a PhD degree will not be considered for this position.
Desired qualifications:
Experience with biosignal processing (EMG, ECG, HRV, IMU) or wearable sensing.
Experience with interactive system design, serious games, or real-time human-machine interfaces.
Experience with AI methods such as generative models, reinforcement learning, online/adaptive learning, or uncertainty quantification.
Research experience in rehabilitation engineering, motor learning, or digital health.
Experience with real-time or embedded systems, prototyping, or open-source development.
Experience with Myoelectric control and in particular with Context-informed Incremental Learning (CIIL)
Language requirement:
Good oral and written communication skills in English
All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control regulation, the Sanctions regulation, and the national security regulation.
What are we looking for in you?
Personal skills:
Strong ability to work purposefully, systematically, and independently.
The applicant's estimated academic and personal ability to complete the project within the time frame.
Very good collaboration skills and a strong interest in working in a multidisciplinary team, including across disciplines and institutions.
Relevance of the proposed project to MishMash's WP3 aims and objectives.
Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal qualifications.
We can offer you
Exciting and meaningful tasks in an organization with an important societal mission, contributing to knowledge development, education, and enlightenment that promote sustainable, fair, and knowledge-based societal development.
An exciting and professionally stimulating working environment, including all the benefits of being part of a large Norwegian AI Centre and its many events, workshops, and career development opportunities.
A built-in international research stay at the University of New Brunswick, Canada.
Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes
Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities
Salary in position as PhD Research Fellow, position code 1017 in salary range NOK from 550 800 - 595 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund
We need different perspectives in our work
UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no.
We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues, could you be the next one?
We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures.
If you have an immigrant background, a disability, or CV gaps (Norwegian), we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian).
The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here.
We hope you will apply for the position with us.
How to apply
The application must include:
Cover letter - statement of motivation and research interests
Research proposal stating research questions and methodological approaches with references, as well as a detailed and feasible progress plan (maximum 14 000 characters (excluding references)). The proposal should clearly specify how the project aligns with MishMash WP3, and is encouraged to articulate connections to WP1 and/or WP7 if any.
CV (summarizing education, positions and academic work - scientific publications)
Copies of the original Bachelor and Master’s degree diploma and transcripts of records
A copy of the Master's thesis, and (if applicable) a list of publications with up to 5 academic works the applicant wishes to be considered by the evaluation committee.
Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)
Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for this job". Foreign applicants should attach an official explanation of their University's grading system.
When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language.
General information
The best qualified candidates will invited for interviews.
Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us.
