Kristin Falk

This PhD research fellow position is based at the Department of Science and Industry Systems , University of South-Eastern Norway , campus Kongsberg. The project sits within SFI CELECT – the Centre for Effective Engineering and Learning in Complex Systems – and links the candidate to a wider doctoral and research network across USN, NTNU, and the University of Agder. The fellow will also be part of the Industrial Research School in Complex Systems (INRESCOS) and the Norwegian Industrial Systems Engineering Research Group (NISE) . The doctoral project focuses on how Norwegian industry can build and develop competencies for systems engineering, AI, and business innovation . The aim is to develop and validate a competency framework and translate it into work-integrated learning for industry. The student will work with CELECT partner companies and academic collaborators to explore competency gaps, effective learning formats for engineers, and ways universities and companies can co-develop learning that has lasting impact. The research is strongly applied and collaborative. The successful candidate will work closely with companies through interviews, surveys, workshops, and pilot courses, and will help shape the final research questions together with the supervisory team and industry partners. The project is embedded in a technology-rich environment at Kongsberg, with connections to major industrial sectors including maritime, defence, aerospace, energy, and subsea technology. The position is part of a larger centre effort that aims to feed results directly into training for engineers across partner organisations. The candidate will contribute to research outputs, participate in common workshops and learning events, and engage in international activities such as conferences and research stays abroad. The project therefore combines systems engineering with competence development, learning design, and industry engagement in a setting where research and practice are intended to inform each other closely.

This PhD Research Fellow position is based in the Department of Science and Industry Systems at the University of South-Eastern Norway, campus Kongsberg, and is embedded in the wider SFI CELECT centre and the Norwegian Industrial Systems Engineering Research Group (NISE). The project focuses on life-cycle perspectives on system qualities , especially how long-living energy, infrastructure, and defence systems can remain changeable and affordable to update over decades. The research addresses a practical systems problem: early architecture decisions strongly influence how easily a system can be modified later, while information about the built system is often lost across handovers and during operation. The PhD will investigate how lightweight architecting, the digital thread, and AI can connect requirements, architecture, and operation across the life cycle, helping engineers reason about trade-offs between future changeability and life-cycle cost. The project is positioned in a strong industrial ecosystem. SFI CELECT brings together USN, NTNU, and the University of Agder together with leading industrial partners, and this PhD will use industry as a laboratory through real cases with companies such as TechnipFMC, Glitre Nett, Herøya Industripark, and Forsvarsmateriell. The student will work closely with engineers and systems architects on development projects, and may also have a research stay abroad. The academic environment combines doctoral training, collaborative research, and cross-institutional activity through CELECT and INRESCOS. The role is structured as organised research training leading toward the doctoral degree, with participation in courses, publications, workshops, and international research activity. The appointment is linked to systems engineering research with strong relevance to long-living technical systems and industrial practice.

University of South-Eastern Norway is advertising a PhD Research Fellow in Systems Engineering at the Department of Science and Industry Systems, campus Kongsberg, Norway. The project focuses on AI tools for early validation and development of complex integrated systems , with an emphasis on data-intensive engineering, digital twins, and design support methods that help engineers explore large design spaces before a system is built. The doctoral project is part of SFI CELECT (Centre for Effective Engineering and Learning in Complex Systems), a Research Council of Norway funded centre bringing together leading industry partners and doctoral researchers across USN, NTNU, and the University of Agder. The fellow will also join the Norwegian Industrial Systems Engineering Research Group (NISE) and the Industrial Research School in Complex Systems (INRESCOS) . Industrial cases will be selected from CELECT partners, and the position is designed around an industry-as-laboratory approach, combining academic research with collaboration in real development projects. The research challenge is to develop AI-supported design methods and tools that can assist early system validation in highly complex, data-driven systems where design and operation are tightly linked and where traditional methods often detect issues too late. The project may explore how such systems are currently designed and validated in industry, and how AI and digital twins can support better early-stage design decisions. The final research questions will be shaped together with supervisors and industry partners. The position is a three-year educational appointment devoted to organised research training. A four-year appointment with 25% career-advancing work may be considered. The fellow must be admitted to the doctoral programme in Technology (Systems Engineering) within three months of starting. The programme includes coursework, an independent thesis, dissemination, a trial lecture, and public defence. The workplace will be shared between campus Kongsberg and one or more partner companies, with time spent at company premises depending on the project. Supervision: the main supervisor is Professor Kristin Falk . The project is embedded in a strong Norwegian technology environment with industry links in maritime, defence, aerospace, energy, and subsea technology. Eligibility highlights: applicants should have a relevant master’s degree (120 ECTS or equivalent), strong academic results (B average or better on master’s degree and thesis), documented methodology knowledge, excellent English, and the ability to work independently as well as collaboratively in an industrial setting. Experience or interest in AI/ML, systems architecting, model-based systems engineering, simulation, and digital twins will strengthen the application. Scandinavian language skills or Norwegian B2 are preferred, and the role also requires eligibility for restricted authorization and export licence/security clearance. Funding: the position is salaried in accordance with the Norwegian State salary scale for PhD research fellows (position code 1017), starting at NOK 550,800 per year, plus pension and standard public-sector benefits. The position is not funded by the EU research framework programme. Deadline: apply by 15 December 2026 at 23:59 (Europe/Oslo). Applications are submitted through Jobbnorge and must include diplomas, motivation letter, language documentation where relevant, publications, references, and supporting documents for foreign qualifications.