Join the team · Open positions
Opportunities
Work with us at the frontier of computational mathematics
At ADAMUS we are constantly on the lookout for talented researchers and professionals to join our teams. We offer a wide range of positions including PhD students, Post-doctoral fellows, and senior Researchers. If you are excited by rigorous mathematical challenges with impact, we would love to hear from you.
Open positions
Research Scientist — Scientific Machine Learning
This position targets the integration of learned surrogate models within certified reduced-basis frameworks. The candidate will have a track record in both numerical analysis and machine learning.
Post-doctoral Fellow — Data-Driven Turbulence Modelling
We invite applications for a two-year post-doctoral fellowship aimed at integrating data-driven closure models into compressible Navier–Stokes solvers. Strong background in CFD and ML required.
Senior Researcher — Computational Mathematics
We are looking for an experienced researcher to lead the development of novel spectral and particle methods for multiscale transport problems, with the opportunity to build and supervise a small team.
Post-doctoral Fellow — Asymptotic-Preserving Schemes
A two-year post-doctoral position to develop and analyse asymptotic-preserving schemes for collisional kinetic models. The fellow will collaborate with partner universities in Leuven and Aachen.
PhD Position in Machine Learning for Kinetic Equations
This interdisciplinary position focuses on physics-informed neural networks and operator-learning architectures for kinetic-theory equations, bridging rigorous numerical analysis and modern deep learning.
PhD Position in Uncertainty Quantification for Multiscale Models
The successful candidate will design Monte Carlo and quasi-Monte Carlo methods tailored to high-dimensional, stiff multiscale systems, with applications in plasma physics and traffic flow.
PhD Position in Structure-Preserving Numerical Methods
We seek a highly motivated doctoral candidate to develop and analyse structure-preserving discretisations for kinetic and fluid equations. The work combines functional analysis with high-performance computing.
Contact us now!
We welcome applications from exceptional candidates at any stage. Send a brief statement of interest and your CV to adamus@unife.it.