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Computational Neuroscience and Inference from data are disciplines that extensively use tools from Mathematics and Physics to understand the behavior of model neuronal networks and analyze data from real experiments. Due to its interdisciplinary nature and the complexity of the neuronal networks, the list of techniques that are borrowed from Physics and Mathematics is an extensive one. Although using tools from standard curriculum of Physics, Mathematics and Engineering is common, more advanced research requires methods and techniques that are not usually covered in any single discipline. 


To fill in this gap, this summer school covers some of the most important methods used in computational neuroscience research through both main lectures and scientific seminars (5-6 main lectures per topic and  1-2 seminars by each invited seminar speaker).

Organizers: Yasser Roudi, Ines Samengo, Nicolai Waniek, Ivan Davidovich and Benjamin Dunn

Tutors: Bautista Arenaza

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Lectures (this is not a final list)

Information theory and inference 

Statistical mechanics of neural networks

Dynamics of neural networks

Dimensionality Reduction

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Invited lecturers and seminars speakers (this is not a final list and might change)

Sara Solla, Northwestern University, USA

Predrag Cvitanović, Georgia Tech, USA
Juan Gallego, Imperial College London, UK

Inés Samengo, Balseiro Institute, Argentina
Yasser Roudi, King's College London, UK

Peter Dayan, Tübingen, Germany

Nicolai Waniek, NTNU, Norway

Li Zhaoping, MPI, Germany
Soledad Gonzalo Cogno, NTNU, Norway

Iván Davidovich, NTNU, Norway

Benjamin Dunn, NTNU, Norway

Nina Miolane, UCSB, USA

Matteo Marsili, ICTP, Italy

Federico Stella, Donders Institute, the Netherlands



Some speakers will join in-person and others remotely. Due to administrative issues, we are currently unable to broadcast the talks openly via Zoom.

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Applications for 2024 are now closed

The deadline for applications was March 31st at 11:59PM CET. The results of the selection process will be communicated by email around mid April.

The summer school is aimed at PhD students, but Master's students and postdocs (as well as those transitioning between any of these) are also welcome to apply.

There are no registration fees for the school. Accommodation and food (except for alcohol) will be covered by the school for all students selected to participate. Participating students must attend the school in person for its whole duration. Students should expect to be assigned a shared bedroom.

Ground transportation between Molde and the Fred Kavli Knowledge Center will be provided by the school on a pre-determined schedule on both arrival and departure days (July 8th and 26th, respectively).

Non-NRSN students: Students that don't belong to NRSN will need to find their own funding to cover their travel expenses from their place of residence to Molde (and back).

NRSN students: NRSN can cover your travel expenses. Please check

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About the Fred Kavli Knowledge Center

The Fred Kavli Knowledge Center is located in the family farm where Fred Kavli grew up. It is surrounded by the scenic area of Eresfjord and is a gathering place for programs that stimulate curiosity, innovation, and big ideas.

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