NTNU, Norway invites online Application for number of Fully Funded PhD Degree at various Departments. We are providing a list of Fully Funded PhD Programs available at NTNU- Norwegian University of Science and Technology, Norway.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: PhD research fellow in Modern Economic History
The Department of Historical Sciences at the Faculty of Humanity offers an exciting 3-year PhD position that gives you the opportunity to develop a strong profile as researcher. The 3-year PhD position is associated with a European Research Council/Horizon Europe research project, entitled “BLOCKADE: The Hidden Weapon. Blockade in the Era of the Two Worlds”. The project explores the impact and legacy of the (sea) blockades during and after both world wars and is undertaken by international teams in four locations, including at NTNU, the University of Freiburg, the University of Amsterdam and the University of Hamburg. For a position as a PhD research fellow, the goal is a completed doctoral education and the attainment of a doctoral degree.
The PhD research fellow will focus on the work package Blockade-induced innovations and imitations, and postwar market integration. The Blockades and the expectation of blockades in the era of the world wars prompted autarky policies, investments in R&D, and import substitution by imitation as well as innovation to cope with scarcity. Whereas some of these innovations and new domestic industries were commercial failures after the war, others became competitive, integrating new (imitative) industries in the world market and crowding out old suppliers. Little is known about the long-term effects of most blockade-induced innovations and the fate of new industries resulting from blockade-induced protection. The work package will use company files relating to two countries affected by the blockade in one of the world wars (e.g. Italy, Norway, Austria-Hungary or Japan, among many others), in order to explain when and why innovations and imitations failed or, by contrast, proved to be of long-term benefit to companies and economies.
Deadline : 30th April 2026
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in Information Structures for Integrated and AI‑Supported Maritime Design
The PhD project will be part of the Norwegian Maritime AI Center that aims to accelerate operationalization of AI in the maritime value chains. The center shall position the maritime sector for accelerated and successful use of AI. The demand for safe and sustainable maritime activities, as well as the shortage of crew and engineers, are key drivers for change in the maritime sector. At the same time, there is a pull for growth, increased efficiency and profitability, while managing volatility in the markets. Moreover, the sector is critically important for global supply chains and security in a tense geopolitical situation. To demonstrate and prototype maritime AI solutions, the center will address a diverse and impactful set of use cases: Logistics, shipping and business transactions; Ship design and construction; Voyage planning and optimization; Condition monitoring and maintenance; Crew training; Maritime traffic and ship surveillance; Decarbonization and energy management; Autonomous ships and remote control.
The research partners are the Norwegian University of Science and Technology, (NTNU), University of Oslo, Oslo School of Architecture and Design, Royal Norwegian Naval Academy, Norwegian Mapping Authority, MET and SINTEF Nordvest. There are about 30 user partners from the maritime sector, in addition to hundreds of members of the Maritime Forum, Blue Maritime, Ocean Autonomy, and Maritime CleanTech clusters. The center will be a hub, orchestrating the interfaces with research partners and user partners to facilitate collaboration, knowledge creation, dissemination, innovation, and sharing of knowledge. The Norwegian Maritime AI Center is funded by the Research Council of Norway and the partners for the period 2026-2030. There will be approximately 25 doctoral scholarships and some postdoc positions.
Deadline : 26th April 2026
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in AI-Enhanced Planning in Shipbuilding Supply Chains
The Department of Department of Mechanical and Industrial Engineering is offering an exciting PhD position within the Norwegian Maritime AI Centre, a national centre with a focus on applied artificial intelligence (AI) in the maritime sector.
The maritime industry is adopting AI technologies. The next decade will bring extensive digitization of operational data in yards, creating opportunities for more data-driven planning. AI can replace or supplement traditional planning approaches, which struggles to manage the uncertainty and variability that are inherent in complex engineer-to-order shipbuilding. Realizing the full potential of AI is both a technical and an integrative challenge. It requires combining what AI excels at, such as pattern recognition and processing data streams, with theories and methods for planning and logistics.
The PhD research will focus on AI-enhanced planning of operations in shipbuilding supply chains, examining how AI techniques can support decision-makers in analyzing real-time and historical data to better coordinate operators, equipment, and facilities, as well as manage operations across multiple projects and supply chain partners. A key part of this research is to investigate how AI can be integrated into planning methods and systems in supply chains, particularly how AI can anticipate disruptions, analyse trade-offs in tactical sourcing decisions, and contribute to improved supply chain performance.
You will join the Production Management Research Group at NTNU, which focuses on the design and planning of production and logistics systems. The research will be carried out together with industry and public partners in the Norwegian Maritime AI Centre. As part of a world-leading research community, you will investigate how AI can reshape planning and logistics in complex shipbuilding supply chains.
Deadline : 21st April 2026
(04) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in Distributed Machine Learning
SURE-AI: a National AI initiative: Six national research centres for Artificial Intelligence (AI) were launched in the Fall of 2025. These centres will foster interdisciplinary collaboration among researchers to address both scientific and societal challenges, develop new technologies, understand the impact of AI, and drive innovation across both the business and public sectors. This initiative is established and financed through the government’s significant investment in artificial intelligence over the next five years
SURE-AI is a Norwegian AI centre funded by the Research Council of Norway (2025-2030). The primary objective is to create a new generation of algorithms for inference and decision-making by pushing the boundaries of the underlying computational techniques. SURE-AI researchers will drive a transformative leap in AI through a groundbreaking Centre initiative dedicated to making AI more efficient, transparent and safe, addressing the critical challenges of resource consumption, behavior unpredictability and ethical alignment with human and societal values. The centre involves senior researchers from well-renowned national and international research institutions, in close collaboration with industry and public sector. Overall, SURE-AI includes 19 national Norwegian partners, as well as researchers from 15 international institutions. More on the project at http://sure-ai.no.
Deadline : 24th April 2026
(05) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in Semantic web for autonomous and adaptable urban services
Funded in the framework of the Driving Urban Transitions (DUT) Partnership (DUT Call 2024), the UrbanBREATH is an interdisciplinary project focused on measuring, modeling and mitigating air pollution in urban environments. We combine low-cost sensing, community engagement and data-driven policy recommendations to create healthier cities.
Ensuring clean air is a critical component of urban ecosystems, as urban air quality significantly impacts the health of city residents and surrounding wildlife. This project aims to develop and provide deployment strategies for air quality monitoring system based on different urban stakeholders (residents, landlords, infrastructure owners, utility companies, recycling companies). The main focus of the project is on monitoring and decision-making based on ventilation systems for the corresponding stakeholders. The UrbanBREATH project is to provide integrated IoT-based monitoring solution to assess specifics of each of the stakeholders. The research hypothesis is that the performance of each of the stakeholders can be derived based on evaluation of the air quality and there exists intelligent automation strategies allowing for optimization of air quality with simultaneous reduction of energy consumption and carbon footprint of buildings.
Deadline : 15th April 2026
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(06) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in parasite and plankton behavioural biology and ecology
The PhD project will be organised under the research group “Fish parasites, health and welfare” and will focus on behaviour and ecophysiology of sea lice and selected zooplankton species. The project will include methodological developments as well as investigations of behavioral responses of the species in question to different stimuli and putting the results in an ecological context. The project will largely rely on laboratory experiments using image and video detection and subsequent analyses using programming. Established cultures of different species will be used, and in addition there will be possibilities for field work.
Deadline : 13th April 2026
(07) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in AI-enabled Hybrid Manufacturing and Remanufacturing Systems
Manufacturing industries are transitioning toward circular production systems, where products and components are reused, repaired, or remanufactured to extend their lifecycle and reduce environmental impact. Remanufacturing is one of the most promising circular strategies, yet its implementation within industrial production systems remains challenging.
Companies are increasingly exploring hybrid manufacturing–remanufacturing systems, where new production and remanufacturing operations coexist within the same production environment. However, these systems introduce significant operational challenges due to uncertainties in returned product condition, quality variability, and unpredictable return flows.
This PhD project will investigate how artificial intelligence and data-driven decision-support tools can support operational decision-making in hybrid manufacturing–remanufacturing systems.
The research will focus on:
• AI-enabled decision support for hybrid manufacturing–remanufacturing systems, supporting operational decisions such as routing, repair, reuse, or remanufacturing of returned components.
• Data-driven assessment of returned product quality and uncertainty, enabling more reliable planning and operational control in circular manufacturing environments.
Digital product passports and industrial traceability systems may be explored as data sources to support these decision-support approaches.
The research will contribute to the development of sustainable and data-driven manufacturing systems and will be conducted in collaboration with industrial partners and international research networks.
Deadline : 11th April 2026
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in bioinspired randomly featured materials
The growing demand for new advanced materials that can serve a variety of strategic fields—e.g., aerospace, marine, and ground vehicle—has pushed the boundary of material science towards a revolution in developing materials that would offer unprecedented combination of properties such as strength and toughness. Recently, a new type of “chaotic” spider webs—webs that exhibit unique patterns—in Nature has been discovered and its complex energy dissipation mechanism has not been fully understood yet. This project will explore a new design strategy for developing lightweight and damage-tolerant materials by extracting design principles of natural web.
The PhD candidate will perform investigation on the unique designs of newly discovered spider web in terms of damage-tolerance and the efficiency of energy dissipation. The developed knowledge will provide design guidelines for high-performance materials to meet industrial needs. A hybrid numerical and data-driven method will be exploited in this project to systematically integrate natural design principles into the development of bioinspired materials. Particularly, artificial intelligence will be exploited as tool to expedite the complex and time-consuming process of material design.
Deadline : 10th April 2026
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(09) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in Rock Engineering for New Hydropower Plants – IV-52/26
The New Hydropower Plants – Design and Construction (RP1.1) Project under FME RenewHydro is dedicated to the development of improved design for future hydropower plants. The project aims to reduce construction costs, environmental impacts, technical risks, improve operational capabilities and ensure functional design that will facilitate long term operation and maintenance with minimum environmental impacts for intakes and outlets, tunnel systems, powerhouse arrangements and pump-turbine submergence.
The work shall be interdisciplinary and review existing design methods for tunnel system and powerhouse cavern and investigate design methods to ascertain minimum required rock stresses (engineering geology), challenge necessary submergence (mechanical/civil), develop new powerhouse arrangements with respect to size and engineering geological perspectives (civil/ engineering geology), tailrace tunnel system arrangements and outlet structures (hydraulic/environmental/ engineering geology), fish friendly pumping intakes (civil/engineering geology/hydraulic/environmental). By considering all aspects, optimized designs and best practice are sought to be found. The new technical design and solutions shall be discussed in workshops with industry experts and ranked according to consensus-based ranking criteria. The scientific results shall be presented in international conferences and published in recognized international journals.
Deadline : 10th April 2026
(10) PhD Degree – Fully Funded
PhD position summary/title: PhD in Economics (EduGAP Project)
The Department of Economics is a seeking committed, curious, and ambitious person to work on the recently awarded Norwegian Research Council project EduGAP. This position is as a three-year PhD candidate.
The project aims to provide causal evidence on the impact of assessment forms on student choices and outcomes, both during schooling, into higher education, and throughout the life course. The project position will be supervised by Professor Colin Green (Department of Economics) and Dr. Jon Marius Vaag Iversen (NTNU Samfunnsforskning & Department of Economics). We are looking for a candidate who wishes to conduct research in applied microeconometrics with a focus on education and labour economics. This project is a collaboration with the University College London and University of Texas-Austin. In addition to providing a range of opportunities to interact with leading international researchers, there will be opportunities to visit these institutions.
We seek an applicant with a master’s degree in economics or a closely related field with excellent results, who wishes to immerse themselves in the subject. Candidates with experience and aptitude in applied econometrics and applied microeconomics are particularly encouraged to apply for this position. The department currently hosts 700 students, including 7 PhD students. The student will become part of an active and inclusive group of PhD candidates at the Faculty of Economics and Management.
Deadline : 9th April 2026
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(11) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in computational mechanics
Join an ambitious research environment at the Department of Structural Engineering at NTNU, where computational mechanics, advanced finite element modelling, and artificial intelligence meet. As a PhD candidate, you will work at the forefront of nonlinear simulation, contributing to the development of next-generation AI-enhanced finite element methods for robust structural design.
You will be part of a dynamic and internationally oriented research group with strong expertise in solid mechanics, constitutive modelling, and high-performance computing. The position offers close supervision, access to modern computational infrastructure, and collaboration opportunities across disciplines — from mechanics to machine learning.
This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You will gain strong expertise in scientific programming, advanced simulation techniques, and AI-driven modelling — skills that are highly attractive both in academia and in high-tech industry.
Are you motivated to take a step towards a doctorate and open up exciting career opportunities? As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, in and outside academia.
Deadline : 8th April 2026
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(12) PhD Degree – Fully Funded
PhD position summary/title: Ph.d. stipendiat i psykisk helse, rus og legemiddelbruk
VINGO-studien er en oppfølgingsstudie av unge voksne som har bodd i barnevernsinstitusjoner i deler av sin oppvekst. Resultater fra studien viser at disse har høy forekomst av traumatiske livserfaringer, psykiske lidelser, risiko for rusavhengighet og mange har stort behov for helse- og sosiale tjenester. Bruken av legemidler i denne gruppen personer kan gi nyttig informasjon om kontakten med helsetjenestene, men det kan også gi svært nyttig kunnskap til helsetjenesten om praksis rundt forskrivning av ulike legemiddelgrupper og risikofaktorer knyttet til dette.
Som stipendiat i dette prosjektet vil du jobbe med data fra VINGO-studien og data fra legemiddelregisteret. Du vil inngå i en tverrfaglig forskningsgruppe med internasjonale samarbeidspartnere.
Stillingen innebærer selvstendig arbeid med opplæring, veiledning og tett oppfølging. Du vil ha ansvar for publisering og forskningsformidling av høy kvalitet. Prosjektet er finansiert av Samarbeidsorganet Helse Midt-Norge.
Deadline : 8. april 2026
(13) PhD Degree – Fully Funded
PhD position summary/title: 2 PhD Candidates in Mathematical Sciences
We have two vacancies for PhD fellowships at the Department of Mathematical Sciences.
Through a PhD fellowship, you will pursue a doctoral education leading to a PhD degree.
The Department of Mathematical Sciences at NTNU is Norway’s largest university environment within mathematical sciences with 75 permanent staff members and more than 55 doctoral students and postdoctoral fellows.
The Department conducts research at an international high level within the disciplines of algebra, analysis, didactics of mathematics, differential equations, geometry/topology, numerical analysis, optimization, and statistics. Part of the research is also carried out in close cooperation with other fields of science and technology at NTNU, as well as in cooperation with industry and external research institutions.
The Department of Mathematical Sciences wants to support excellent and highly motivated candidates within any of the Department’s main research disciplines. For further information about the different research disciplines see https://www.ntnu.edu/imf/research.
Are you motivated to take a step towards a doctorate and open exciting career opportunities? As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, in and outside academia.
Deadline : 8th April 2026
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in RF/antenna design for GNSS reflectometry from small satellites
he signals originating from the global navigation satellite systems (GNSS) when they are reflected from the Earth, contain information about the geographical area the signals are reflected by. For signals reflected by the ocean, we can infer wave height, sea ice coverage and winds using GNSS-reflectometry (GNSS-R). In this project, we want to go further and investigate if we can use these signals of opportunity to detect objects, such as ships. Actions by so-called “dark ships”, meaning ships that operate with no AIS transponder, may contribute to illegal fishing, trafficking, sabotage and other less desired activities. Currently, there are several systems in use to monitor global ship traffic, each with different properties. Optical systems may provide excellent resolution on a cloud-free day. Synthetic aperture radars (SAR) deliver image products even through clouds, but they are expensive. Our main research question is: How can small and relatively cheap satellites with passive radio payloads utilize reflected signals of opportunity to contribute to a better maritime situational awareness?
As a PhD candidate in this project, your work will be to research how this monitoring can be done, and how it can feed into a larger system. Your focus will be on RF- and antenna design for reception of reflected GNSS signals. The research will also involve using software-defined radios (SDR) and digital signal processing for antenna beamforming.
Deadline : 7th April 2026
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in Digital Twins and AI for Cultural Heritage Preparedness
The position is funded by the Horizon Europe project HERITWIN (2025–2028), which includes 17 European partners and aims to validate advanced digital infrastructure for cultural heritage through five national pilots (Sweden, Norway, Spain, UK, and Greece). The Norwegian pilot develops and validates:
- Digital twin development for heritage risk preparedness
- AI-based predictive monitoring (humidity, flooding, structural stress)
- Integration of GIS/BIM, LiDAR and IoT telemetry
- Federated data architecture and semantic interoperability
- Explainable and trustworthy AI aligned with European regulations
The PhD candidate will contribute to modelling, system validation, and scientific dissemination within the project framework.
Deadline : 7th April 2026
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in magnetohydrodynamic modeling of electric arcs in silicon furnaces
The successful candidate will be part of the project SAPPHIRE (https://sapphire.norceresearch.no/).
SAPPHIRE aims to contribute to cleaner and more energy-efficient metal production. We will deepen the understanding of how the electric energy that drives the smelting processes interacts with the process chemistry. This knowledge will be used to improve the stability of smelting furnaces, thereby reducing the specific energy consumption (kWh/kg alloy produced); and enabling the transition to bio-based reductants used for decarbonization.
SAPPHIRE is led by NORCE. NTNU is a research partner, and our international collaboration includes Reykjavík University and the University of Padova. Our industrial partners Elkem ASA, Eramet Norway AS, Finnfjord AS, and Wacker Chemicals Norway AS support the project through the Norwegian Ferroalloy Producers’ Research Association (FFF).
Deadline : 6th April 2026
(17) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in Trustworthy AI-Enabled Signal Analysis for Next-Generation Wireless Systems
Are you looking for a PhD opportunity that combines rigorous AI research with high-impact problems in next-generation wireless systems? We are recruiting a talented and motivated PhD student for a Research Council of Norway-funded project in collaboration with NTNU and SINTEF Digital. The research focuses on advanced signal analysis and machine learning methods that enable robust operation and service continuity in future wireless networks under challenging radio conditions.
As a PhD student, you will develop state-of-the-art learning and inference methods to detect and characterize anomalous radio behavior and to design algorithms that remain reliable under practical constraints. Depending on background and interests, the work may involve robust detection under distribution shifts and unseen interference conditions, resilient federated/decentralized (collaborative) learning, and reinforcement learning for adaptive decision-making. A key aim is to connect wireless phenomena to learning robustness by combining physical-layer signal structure and signal-processing insights with trustworthy learning principles.
You will join a dynamic, collaborative team conducting rigorous AI and signal processing research with clear relevance to future wireless systems. The work emphasizes principled modeling, reproducible experimentation with open datasets and simulations, and publication-ready contributions targeting leading venues in machine learning and wireless communications. You will also have opportunities for international collaboration with leading research groups through joint publications, visits, and conference presentations.
Deadline : 6th April 2026
(18) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in Registry-Based Research on Migraine Treatment and Outcomes
Chronic migraine affects millions globally, causing substantial disability and healthcare burden. Anti-CGRP monoclonal antibodies (mABs) have transformed migraine prevention, but questions remain about optimal treatment duration and outcomes after discontinuation or reinitiation.
This project will evaluate the effects of anti-CGRP mABs on acute migraine medication use across different treatment trajectories—initiation, discontinuation, and reinitiation. Using comprehensive nationwide Norwegian registry data, the study will provide insights into real-world effectiveness across different treatment phases, informing clinical decision-making, guide treatment strategies, and contribute to improving care for patients with chronic migraine.
We are looking for a motivated PhD student who will be part of methodologically strong, interdisciplinary and international research environment at NorHead. Our collaborators include leading research groups in the UK, Denmark, and Spain – including the world-renowned High-Dimensional Neurology Group at UCL Queen Square Institute of Neurology in London.
Deadline : 6th April 2026
(19) PhD Degree – Fully Funded
PhD position summary/title: PhD in Economics
Do you have a master’s degree in economics or a closely related field with excellent results and wish to immerse yourself in the subject through independent research? If yes, then you might be the person we are looking for!
The Department of Economics is looking for a committed, curious, and ambitious person for a three- year position as a PhD candidate.
The position is an open position in Department of Economics. This is a unique opportunity to contribute to high-quality international research across a range of economic topics. We are looking for candidates who wish to conduct research in one of the areas of research in the department. Our main research profile is in the areas of applied microeconomics, such as public economics, political economy, and behavioral economics. Other areas are environmental and resource economics, development economics, international economics, macroeconomics and finance.
Deadline : 2nd April 2026
(20) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in Biological Oceanography: Zooplankton and its role in the carbon pump
We invite applications for a PhD candidate to join an interdisciplinary research project focused on zooplankton ecology and its role in the oceanic biological carbon pump under the supervision of Associate Professor Jose Landeira and co-supervisor Associate Professor Kang Nian Yap . Oceans have sequestered approximately 30–50% of anthropogenic CO₂ since the beginning of the industrial revolution, mitigating the rise in atmospheric CO2 and, consequently, global warming. However, the mechanisms through which carbon is transported into the deep ocean remain poorly understood.
The project will investigate how zooplankton contributes to carbon sequestration through vertical migrations, using a combination of optical and acoustic instruments to observe and quantify their dynamics in the water column. A key objective is the development and improvement of physiological proxies and endpoints to better estimate zooplankton respiration and its impact on oceanic carbon fluxes. The position offers training in field observations, advanced instrumentation, experiments with zooplankton organisms and physiological analyses within an international research environment. This position will contribute to the strategic program Polhavet 2050.
Deadline : 2nd April 2026
(21) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in data acquisition and analyses in tunnelling projects
unnelling projects generate large volumes of data, (e.g. MWD, mapped geological data, rock support, rock mass grouting, geometrical design and as-built data). The value of the data is often not fully realized as it is fragmented across systems and formats, difficult to link in time and space and locked into manufacturer-specific tools. This PhD project aims to redefine how tunnel data is interpreted, integrated and utilized. One research path can be to develop a complete digital workflow that transforms raw data acquisition to machine learning interpretation to 3D geometry and quality models to machine learning decision support. The PhD project will be carried out in close cooperation with Norwegian tunnelling contractors, project owners and system manufacturers.
Deadline : 1st April 2026
(22) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in Visualisation of AI Advice for Safety-Critical Maritime Decision Support
This PhD project will explore how to visualise advice given by AI systems in a way that enables seafarers to understand the rationales and uncertainties behind the advice in an intuitive manner. The goal is to enable seafarers to reap the benefits of AI-based decision-support systems without compromising operational safety.
The AI systems to be explored may include:
- AI-based weather-routing for determining optimal routes under changing conditions
- AI-based wind-assisted propulsion decision support for optimally deploying wind-sail propulsion according to weather conditions
The project will develop, prototype, and evaluate visual and interaction concepts that make AI advice actionable, interpretable, and appropriately calibrated to user needs in safety-critical settings (e.g., supporting correct reliance, timely challenge, and effective override when needed)
Deadline : 1st April 2026
(23) PhD Degree – Fully Funded
PhD position summary/title: PhD Candidate in Risk-Consistent Design of Protection Structures for Climate-Adapted Infrastructure
Are you ready to take on the challenge of a PhD and contribute to advancing resilient and sustainable infrastructure? As a PhD Candidate with us, you will work toward earning your doctorate while developing strong expertise in probabilistic modelling, structural reliability, and decision-oriented engineering.
We are seeking a highly motivated candidate with a background in structural engineering, mechanical engineering, computational mechanics, or related fields who wants to contribute to developing the next generation of risk-informed design methodologies for infrastructure exposed to natural hazards and climate change.
Deadline : 1st April 2026
(24) PhD Degree – Fully Funded
PhD position summary/title: SFI FAST: PhD Candidate in Materials Physics
Studies of phase formation, evolution of microstructure and casting defects in high-pressure die casting of recycled aluminium alloys.
The position is a 3-year doctoral research fellowship starting in the autumn of 2026. The PhD candidate will be embedded in the solidification research activities of SFI FAST, working in close collaboration with project partners from NTNU and SINTEF, and with leading Norwegian and international industrial partners in the aluminium value chain.
The PhD candidate will use advanced experimental techniques to study the formation and evolution of solidification microstructures and defects in high-pressure die-cast products, made from aluminium alloys containing a considerable fraction of post-consumer scrap. The research will focus on microstructure and defect formation, how the outcome of these processes is affected by the inclusion of recycled material, and how processing parameters might be altered to obtain components which meet with the end-user requirements.
The overall aim of the activity is to drive the science of future alloys and transform Europe’s capacity in advanced metal manufacturing towards a greener future. Ability to replace parts made by joint components of wrought alloys with components made by shaped castings is considered a pivotal element in recycling of post-consumer scrap and essential for the establishment of a more circular aluminium economy. The scientific and technical challenge is to handle the increase in chemical impurities arising from the inclusion of scrap, and to control the processing parameters such that the structural integrity of the cast components can meet with the demands to performance.
Deadline : 31st March 2026
About NTNU- Norwegian University of Science and Technology, Norway- Official Website
The Norwegian University of Science and Technology is a public research university in Norway with the main campus in Trondheim and smaller campuses in Gjøvik and Ålesund. The largest university in Norway, NTNU has over 8,000 employees and over 40,000 students. NTNU in its current form was established by the King-in-Council in 1996 by the merger of the former University of Trondheim and other university-level institutions, with roots dating back to 1760, and has later also incorporated some former university colleges. NTNU is consistently ranked in the top one percentage among the world’s universities, usually in the 101–500 range depending on ranking.
NTNU has the main national responsibility for education and research in engineering and technology, and is the successor of Norway’s preeminent engineering university, the Norwegian Institute of Technology (NTH), established by Parliament in 1910 as Norway’s national engineering university. In addition to engineering and natural sciences, the university offers higher education in other academic disciplines ranging from medicine, psychology, social sciences, the arts, teacher education, architecture and fine art. NTNU is well known for its close collaboration with industry, and particularly with its R&D partner SINTEF, which provided it with the biggest industrial link among all the technical universities in the world. The university’s academics include three Nobel laureates in medicine, Edvard Moser, May-Britt Moser and John O’Keefe.
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