PhD position, Dept. of Mathematics, University of Bergen, Norway

The Department of Mathematics invites applications for a PhD Research Fellow in Applied and Computational Mathematics. This is a 3-year position funded by the University of Bergen, with the possibility of a 4th year dedicated to career development (e.g., teaching experience). You’ll be part of the Center for Sustainable Subsurface Resources (CSSR) – a national research hub funded by the Norwegian Research Council. CSSR’s mission is bold: develop cutting-edge digital solutions to drastically reduce Norway’s offshore emissions. To support the goals of CSSR, this project aims to develop, analyze and implement new nonlinear iterative solvers, with the goal of exploiting models of various complexity, ranging from high-performance computing, via reduced-order models to data-driven (machine-learned) representations. In particular, we are interested in the joint applicability of such models and to what extent simpler models (possibly based on machine learning) can be integrated into full-physics simulation. Your research will directly contribute to this transformative goal. Your role: -Develop and analyze nonlinear and linear solvers in the context of multi-model analysis of and simulation of subsurface operations - Build on a theoretical foundation from numerical and functional analysis - Build on the literature related to linear operator preconditioning and nonlinear preconditioners for Newton methods - Use concrete model problems and numerical examples to guide and prototype the development For more information on the position and how to apply, please check out: https://www.jobbnorge.no/en/available-jobs/job/292201/phd-research-fellow-in- applied-and-computational-mathematics-cssr ------------------------------------------------------- From: Fred Roosta fred.roosta@uq.edu.au Date: January 03, 2026 Subject: PhD Opportunity in Mathematical Optimisation at The University of Queensland (Australia) We are offering a fully funded PhD position in the School of Mathematics and Physics at The University of Queensland, focused on the development and analysis of next-generation Newton-type optimisation methods. The project addresses fundamental questions in large-scale optimisation and numerical linear algebra, with strong connections to modern machine learning. Applicants should have a strong background in applied mathematics, optimisation, linear algebra, or closely related areas, with experience in programming (e.g. Python). The position is supported by a competitive scholarship covering tuition fees and a living stipend. Further details and application instructions are available on the project webpage: https://study.uq.edu.au/study-options/phd-mphil-professional- doctorate/projects/next-generation-newton-type-methods-minimum-residual- solver