Simula Research Laboratory AS
Position Description
We are pleased to announce a new PhD Research Fellowship in the Department of Numerical Analysis and Scientific Computing at Simula Research Laboratory (Simula) for a highly-motivated and self-driven PhD student with strong intellectual curiosity and interest in the mathematical foundations of artificial intelligence. The position is part of the National Norwegian Center for Sustainable, Risk-averse and Ethical AI (SURE-AI), funded by the Research Council of Norway (RCN) (2025-2030), coordinated by Simula.
Simula is a leading Norwegian research institute known for its excellence in cutting-edge ICT with a strong track record of top evaluations, active international collaborations, and success in significant funding initiatives, including European and National RCN grants. Simula is committed to supporting talent through a variety of PhD and postdoctoral programs and provides valuable research infrastructure, such as the national HPC facility, eX3.
Job Description
We are looking for a PhD candidate to join our team to work on exciting new topics in the numerical analysis of constrained variational problems with pointwise inequality constraints such as elliptic and parabolic variational inequalities, nondivergence form nonlinear PDE, and select problems from PDE-constrained optimization. At Simula, the candidate will work in the research team led by Thomas M. Surowiec, which will include a postdoctoral fellow working on similar topics, two adjunct professors, and several international partners. The PhD candidate will also be expected to be enrolled in the PhD program at the Department of Mathematics at the University of Oslo, a premier European research environment that combines a rich academic heritage with a forward-looking focus on innovation in pure and applied mathematics. A strong background in mathematics is essential.
- Adaptivity and algorithmic fine-tuning techniques.
- Large-scale numerical optimization algorithms for risk-averse training.
- Quantitative stability and distributional robustness of stochastic programs.
- Asymptotic behavior of predictive energy landscapes in dynamic environments.
Desired Skill Sets and Competencies criteria
We will consider candidates who have completed (or will have completed by June 2026) a Master’s degree (or equivalent) in Mathematics, Applied Mathematics, Computational Science, or Physics. The successful candidate will have a solid theoretical foundation in one or more of the topics: Optimization, Real & Functional Analysis, Probability Theory or Numerical Analysis. More specifically, we are looking for candidates with competency in at least one of the following areas and a willingness to learn the others:
- Stochastic Algorithms & Adaptivity
- Risk-Averse Optimization and Distributionally Robust Optimization
- Quantitative Stability Analysis for Stochastic Programs
- Variational Analysis
- Proficiency in a high-level programming language (e.g., Python, Julia, C++).
We are not accepting applications for this job through MathJobs.Org right now. Please apply at https://www.simula.no/careers/job-openings/phd-position-in-foundations-of-mathematical-optimization-for-artificial-intelligence-sure-ai
- Contact: Thomas Surowiec
- Email:
- Postal Mail:
- Kristian Augusts gate 23
0164 Oslo
Norway
- Kristian Augusts gate 23
- Web Page: simula.no