About this role
This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. Video: https://youtu.be/Xt-yHCN5QS0 About the position aiD – AI for Decisions – is one of Norway's new national AI research centers, funded by the Research Council of Norway and industry partners. Led by NTNU and SINTEF, the center brings together 13 research partners and more than 60 partners from industry and the public sector. All open positions will be cross-linked on the aiD website aid-center.no The successful applicant will work at NTNU in Trondheim. The Department of Mathematical Sciences, NTNU, will host the PhD position. The topic of the PhD fellowship is at the interface of numerical mathematics, agentic and generative AI models, and computer science. A successful candidate will be offered a three-year position, which could potentially be extended with career promotion work like teaching duties. 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. Your immediate leader will be the Head of Department. About the project Many critical decisions in science and engineering, from managing power grids to planning subsurface energy operations, depend on computational models that are inherently uncertain. Uncertainty quantification (UQ) seeks to characterize and propagate this uncertainty but translating it into actionable risk measures remains computationally demanding and methodologically challenging. In realistic applications, uncertainty arises from multiple sources, including parametric uncertainty, model-form and structural assumptions, numerical discretization, and incomplete or noisy observations. Addressing these uncertainties typically relies on ensemble-based simulations using computationally expensive high-fidelity models. This PhD project addresses this challenge by researching agentic programming frameworks for decision-oriented uncertainty and risk quantification, in which multiple specialized AI agents collaborate to design, execute, and evaluate UQ workflows under computational constraints. Rather than automating predefined pipelines, the agents act as meta-decision-makers, reasoning about modelling assumptions, approximation levels, and the choice of risk measures considering both decision objectives and available resources. The central scientific aim of the PhD project is to establish formal links between uncertainty representations, risk measures, and downstream decisions, and to study how agentic reasoning can navigate trade-offs between interpretability, statistical reliability, and computational feasibility – and to develop principled criteria for when a given risk measure is well-founded given available data and resources, and when alternative approximations should be considered. Duties of the position Complete the doctoral education until obtaining a doctorate. Conducting high-quality research within the scope of the project. Contributing to research publications in leading international journals and conferences. Participating in international activities such as conferences, workshops and possible research stays abroad. Disseminating research results to both scientific and broader audiences. Collaborating with academic and industrial project partners. Implementing and testing algorithms in high-performance open-source scientific software. Be prepared for changes to your work duties after employment. Required selection criteria You must have a relevant Master's degree in mathematics or equivalent. Your education must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level. Master students can apply, but the master's degree must be obtained and documented before starting the position and no later than 01.09.2026. You must have a strong academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale . If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker grade background, you maybe considered if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme ( https://www.ntnu.no/studier/phma ). You must have documented programming experience relevant to scientific computing, for example in Python, MATLAB, Julia, C++ or similar languages. You must have good written and oral communication skills in English. PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application”. The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position. Preferred selection criteria It is an advantage if you have experience with one or more of the following topics: numerical methods for (partial) differential equations. optimization or inverse problems. data assimilation or uncertainty quantification. agentic and generative AI. solid, structural, or fluid mechanics. adjoint methods, automatic differentiation, or differentiable programming. scientific software development, including reproducible workflows and version control. high-performance computing or parallel computing. It is also an advantage if you have experience with publication-oriented research work and collaboration in international research environment