Kshitij Sharma
6 months ago
PhD Candidate in Multi-Agent Communication to Enhance Human Learning Norwegian University of Science and Technology in Norway
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
December 31, 2026Country
Norway
University
Norwegian Institute of Science and Technology

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About this position
The Department of Computer Science at the Norwegian University of Science and Technology (NTNU) invites applications for a PhD Candidate position in Multi-Agent Communication to Enhance Human Learning. This opportunity is part of the newly established AI Centre for the Empowerment of Human Learning (AI LEARN), a national initiative dedicated to advancing responsible, human-centered artificial intelligence to empower learning in society. The centre is funded through a significant government investment in AI and aims to foster interdisciplinary collaboration, foundational research, and responsible innovation.
The PhD project is associated with the Technological Advancement cluster of AI LEARN and focuses on developing advanced, human-centered AI technologies to support and enhance human learning. The successful candidate will design, develop, and evaluate multi-agent systems and communication protocols, aiming to create innovative educational technologies and adaptive learning experiences. Research activities will include training AI models using supervised and unsupervised methods (such as Retrieval-Augmented Generation, Low-Rank Adaptation, Direct Preference Optimization, and Reinforcement Learning from Human/AI Feedback), conducting participatory design workshops, implementing services and interfaces, planning and executing case studies, and analyzing empirical data from collaborations with schools and public/private sector partners.
The position is based in the Software Engineering research group at NTNU and offers a dynamic, international research environment. The PhD candidate will participate in collaborative activities within the AI LEARN centre, attend international conferences, and contribute to dissemination and communication efforts. The employment period is three years, with the possibility of extension to a fourth year if the candidate undertakes additional duties. The gross annual salary is normally NOK 550,800, with a 2% deduction for the State Pension Fund. The position is conditional on external funding.
Applicants must hold a Master's degree in Computer Science or a closely related field (with a focus on Machine Learning, Artificial Intelligence, or Learning Technology), corresponding to a five-year Norwegian program with 120 credits at the master's level. Candidates must have a strong academic record (average grade B or better), solid knowledge of quantitative and qualitative research methods, and excellent written and oral English skills (with specific minimum test scores required). If not proficient in Norwegian, Swedish, or Danish at level A2, candidates must complete Norwegian language courses during employment. Admission to the IE faculty Doctoral Programme in Computer Science is required within three months of employment. Preferred qualifications include research assistant experience, relevant publications, and presentation skills in Norwegian/Scandinavian.
NTNU offers a supportive and inclusive work environment, career guidance, and access to employee benefits. The university values diversity and encourages applications from candidates of all backgrounds. The position is located in Trondheim, a vibrant city known for its rich cultural scene, excellent quality of life, and strong technology sector.
To apply, submit your application electronically via Jobbnorge.no, including all required documents (transcripts, diplomas, CV, thesis, essay, cover letter, publications, and references) by the deadline of 12 December 2025. For questions about the position, contact Professor Kshitij Sharma at [email protected].
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
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