Brenner du for å skape smartere og mer bærekraftige løsninger? Ønsker du å jobbe tett med ledende forskere og noen av Norges mest innovative industribedrifter?
Nå kan du bli en nøkkelperson i utviklingen av fremtidens systemer, produkter og arbeidsformer.
Ledige stillinger
Vi søker ti ph.d.-kandidater til SFI CELECT – Senter for systeminnovasjon frem mot april 2026.
PhD position 1: Human–AI Decision‑Support for Efficient Value Chains of Complex Products - NTNU
The PhD will utilize and develop human‑centric AI decision-support tools for analyzing and designing efficient and sustainable value streams across various complex industrial supply chains. The main focus is integrating product and process requirements/specifications, logistics resilience, and sustainability into a unified multidimensional modelling framework, with specific emphasis on synergies between defense, manufacturing, maritime and public sectors. The candidate will build and verify a digital decision-support platform, integrating simulation, optimization, and ethical AI for joint human–AI evaluation of supply chain and lifecycle trade-offs (e.g., defense supply resilience, maritime logistics sustainability, manufacturing flexibility, public procurement ethics).
The candidate will work in close collaboration with industrial partners and needs to be responsible for reporting progress and delivering outputs to the CELECT centre.
Application deadline: 20.03.2026
PhD position 2: Next generation knowledge management: Digital tools and organizational learning as complementary capabilities for effective product development - NTNU
This PhD will research how new, enabling digital tools and digital threads can be effectively integrated into work flows in new product development (NPD) to provide a robust basis for organizational learning.
The possibilities to acquire knowledge from inside and outside the organization for the design and development of new products have increased dramatically in recent years. Despite this shift, however, long-time established NPD methods that form the basis for company practices have virtually remained unchanged with their focus on building capabilities for inside knowledge transformation. In response, this PhD will research how organizations can sustain competitive advantage by leveraging organizational learning in today’s digital NPD context, where project learning increasingly requires openness and rapid knowledge acquisition, often from outside the organization.
Relevant research questions are: What are (the characteristic of) ‘organizational learning’ in today’s digital era? How can it be reinforced? How can organizations effectively convert and manage knowledge acquired for decision support across NPD projects into improved capabilities for executing future projects and sustained competitive advantage?
Application deadline: 20.03.2026
PhD position 3: Knowledge-Based Development (KBD) for Instant Decision Support in digitally supported NPD processes - NTNU
The aim of this PhD is to develop effective knowledge-based strategies for improved decision support in NPD processes. The PhD will develop, test and verify the next generation platform for improved decision support in NPD, bridging theory, practices, processes, people and digital tools, and equipping companies with the absorptive capability necessary to effectively navigate the increasing product-service lifecycle responsibility and complexity in various company-business contexts.
This position will complement PhD position 2 above, which focuses more on the organizational learning dimension, by primarily focusing on how NPD teams efficiently can acquire information and knowledge to support instant decision making in projects.
Some main research questions:
What are the main components of a knowledge-based development framework (where digital tools play an increasingly important role)? How can organizations enable interoperability between people, processes and IT/AI tools within such a framework? How do contextual factors play a role for implementation of such a framework? How can we balance between standardized core components and localized adaptions in companies operating globally?
Application deadline: 20.03.2026
PhD position 4: Strategies for leveraging cross-functional knowledge flows in digitally supported NPD processes - NTNU
Since the outcome of NPD processes is not only the physical artifact but also the creation, recombination and transfer of knowledge, cross-functional knowledge flows are central to NPD effectiveness (quality of decisions and solutions) and efficiency (speed and ‘first-time-right’).
This PhD will research how such cross functional knowledge flows can be enabled and leveraged in contemporary NPD settings where collaboration is increasingly mediated by shared digital tools rather than co-located interaction. Accordingly, s/he will investigate how organizations can make NPD work processes more productive by better understanding where digital tools has their limitations and which countermeasures that can be established to improve interactions across functional boundaries to make work flows more tangible and transparent with regards to identifying waste sources and lack of value.
Application deadline: 20.03.2026
PhD position 5: Generative AI for Systematic Concept and Architecture Exploration in Early-stage Product- and System Design - NTNU
Generative AI is emerging as a powerful enabler for systematic concept and architecture exploration in early-stage product design, where the ability to rapidly explore and structure large design spaces is critical. By supporting the formalization of requirements, the generation of diverse solution concepts, and the synthesis of alternative system architectures, generative AI has the potential to augment human designers’ capacity to reason across functional boundaries and make informed trade-offs early in development. However, current applications remain largely ad-hoc, with limited integration into structured design processes and weak support for verification, traceability, and decision-making.
This PhD will investigate how generative AI can be methodically embedded as tools/methodologies into early-stage product and system design workflows to improve the breadth, quality, and transparency of concept and architecture exploration, while accounting for the limitations of digitally mediated design work.
The candidate will plan and conduct empirical studies and case-based research with research and industry partners, including mapping current practice, introducing method elements in real design projects, and evaluating effects on design quality, development speed, traceability, and robustness of decisions.
Application deadline: 20.03.2026
PhD position 6 & 7: PhD Research Fellow in Intelligent Mechatronics - UIA
The PhD candidate will contribute to the CELECT work package on AI-Assisted Engineering.
The research will focus on developing AI-assisted methods for parallel hardware-software co-design of mechatronic systems, enabling virtual prototyping and simulation-driven development from early design stages. The candidate will develop methods that bridge mechanical, electrical, and control domains, improving design quality, traceability, and decision-making. The resulting virtual prototypes will establish the digital foundation that can evolve into digital twins upon physical deployment.
The research will be conducted in close collaboration with industry partners and fellow PhD candidates across the three partner universities. In particular, the candidate will work closely with a PhD candidate at NTNU focusing on AI-assisted concept and architecture exploration in product and system design. The candidate will work within an industry-as-laboratory approach and is expected to contribute to the CELECT research community, including reporting progress and delivering outputs to the centre.
The position is connected to the scientific field of Mechatronics, within the Specialisation in Engineering Sciences.
A prerequisite for employment is that the candidate is to be admitted to UiA’s PhD programme at the Faculty of Engineering and Science.
Application deadline: 31.03.26
Hva du kan jobbe med
Som ph.d.-kandidat vil du bidra til forskning som gjør norsk industri mer konkurransedyktig og fremtidsrettet. Her er hva du kan jobbe med.
-
Komplekse systemer og helhetlig tenkning
Hvordan modellerer og forstår vi store, teknologiske systemer, fra design til drift? Du forsker på hvordan vi kan håndtere kompleksitet og ta bedre beslutninger. -
Systeminnovasjon og tverrfaglig samarbeid
Hvordan samarbeider mennesker, bedrifter og kunstig intelligens best i utviklingen av nye løsninger? Du utforsker nye metoder som styrker tverrfaglighet. -
Produktutvikling for fremtiden
Hvordan lager vi produkter raskere og mer bærekraftig? Du forsker på prosesser, digitale verktøy og beslutningsstøtte som kutter tid og kostnader. -
Kunstig intelligens i ingeniørfag
Hvordan kan kunstig intelligens (KI) gjøre ingeniører bedre? Du vil bidra til å utvikle KI-rammeverk som støtter design, samarbeid og problemløsning.
Hvem vi ser etter?
Du passer godt i rollen hvis du
- har mastergrad innen ingeniørfag, teknologi, systemtenkning, informatikk eller lignende
- liker å se helheten og forstå sammenhenger
- trives med både selvstendig arbeid og samarbeid på tvers av fag
- har interesse for innovasjon, bærekraft og teknologiutvikling
- kan sikkerhetsklareres til nivå Begrenset
Dette får du hos oss
- En unik mulighet til å påvirke hvordan Norge utvikler komplekse systemer og produkter.
- Et forskningsmiljø med høy faglig kvalitet ved USN, NTNU eller UiA.
- Tett samarbeid med 22 industripartnere, blant annet Kongsberg Gruppen, Siemens Energy, Nammo og TechnipFMC.
- Tilgang til moderne laboratorier, KI-verktøy og sterke fagmiljøer.
- Konkurransedyktige betingelser og solid faglig veiledning.
Har du spørsmål?
Henvend deg til kontaktperson som er oppført i hver stillingsannonse.
Våre samarbeidspartnere
FFI, H. Henriksen, KDA, Nammo, Forsvarsmateriell, Knightec, Hive, Nymo, Optime Subsea, Siemens Energy, TechnipFMC, Brudeli, IDT, cDynamics, Pioneer Robotics, Herøya Industripark, Sirkulære Rjukan, Adapa360, Kongsberg kommune, Buskerud fylkeskommune, Telemark fylkeskommune, Vestfold fylkeskommune, Kongsberg Maritime.