DIScover is a centre in mathematical sciences that transforms how we model and understand dynamical systems shaped by uncertainty. From turbulent ocean flows and neural activity to language processing, these systems demand tools that go beyond traditional methods. DIScover fuses deterministic mathematics, stochastic analysis, and data-driven learning to uncover hidden dynamics and build interpretable, low-dimensional models from complex, noisy data.

In an open case hub, we will explore real-world cases that test and unite new theory with real-world settings: reconstructing fluid motion from wave tank experiments, decoding brain signals during sleep and movement, and revealing how the brain processes language. These challenges push the boundaries of current methods and open new paths in fluid mechanics, neuroscience, and neurolinguistics.

Anchored in Trondheim, DIScover unites top experts in the mathematical disciplines of partial differential equations, spatio-temporal statistics and numerical analysis with the applied sciences of fluid mechanics, neuroscience and neurolinguistics. The centre will train PhD candidates and postdocs for future challenges in mathematical modelling, run workshops, winter schools and conferences, and build strong ties to other scientific disciplines and international partners. With access to cutting-edge labs and high-performance computing, DIScover is set up to develop the next generation of mathematical tools for data-driven problems.

DIScover will create the next-generation models with uncertainty by uniting deterministic, stochastic and data-driven methods in mathematical sciences.

The secondary objectives to achieve this primary goal are:

• To build data-driven partial differential equations for systems with unknown laws.
• To analyse and predict dynamics by integrating stochastic equations with statistical models.
• To enhance data-driven methods with physical constraints and geometry.
• To validate and advance models and methods through an interdisciplinary platform for dynamical discovery in real-world settings.