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CAJAL COURSE in Computational Neuroscience

6-26 August 2017, Champalimaud Centre for the Unknown, Lisbon, Portugal

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When

Aug 06, 2017 12:30 AM to
Aug 26, 2017 09:30 AM

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Applications deadline: 20 March 2017 (midnight, CET time)

DIRECTORS
• Gilles Laurent (MPI Brain Research, Frankfurt, Germany)
• Jakob Macke (Research Center Caesar, an associate of the Max Planck Society, Bonn, Germany)
• Christian Machens (Champalimaud Centre for the Unknown, Portugal) 

Computational Neuroscience is a rapidly evolving field whose methods and techniques are critical for understanding and modelling the brain, and also for designing and interpreting experiments. Mathematical modeling is an essential tool to cut through the vast complexity of neurobiological systems and their many interacting elements.

This three-weeks school teaches the central ideas, methods, and practice of modern computational neuroscience through a combination of lectures and hands-on project work. Each morning is devoted to lectures given by distinguished international faculty on topics across the breadth of experimental and computational neuroscience. During the rest of the day, students work on research projects in teams of 2-3 people under the close supervision of expert tutors and faculty. Research projects will be proposed by faculty before the course, and will include the modeling of neurons, neural systems, and behavior, the analysis of state-of-the-art neural data (behavioral data, multi-electrode recordings, calcium imaging data, connectomics data, etc.), and the development of theories to explain experimental observations. 

The course is designed for graduate students and postdoctoral fellows from a variety of disciplines, including neuroscience, physics, electrical engineering, computer science, mathematics and psychology. Students are expected to have a keen interest and basic background in neurobiology, a solid foundation in mathematics, as well as some computer experience. A four-day pre-school in mathematics and programming is offered for students that want to catch up on their math and programming skills.  A maximum of 24 students will be accepted. Students of any nationality can apply. We specifically encourage applications from researchers who work in the developing world. Stipends are available.

More information on the course website,  http://www.ccn.pt

Apply here:  http://www.fens.org/Training/CAJAL-programme/CAJAL-Courses-2017/CCCN2017/

Contact address: Simone Zacarias,  simone.zacarias@research.fchampalimaud.org


Confirmed faculty:

Alberto Bernacchia, University of Cambridge, UK 
Anne Collins, UC Berkeley
Claudia Clopath, Imperial College London, UK
Sophie Denève, Institut d'Etudes de la Cognition (IEC), France
David Fitzpatrick, Max-Planck Florida Institute for Neuroscience, USA
Julijana Gjorgjieva, Max Planck Institute for Brain Research, Germany
Pedro J. Gonçalves, Research Center Caesar, an associate of Max Planck Society, Germany
Richard Hahnloser, Institute for Neuroinformatics, ETH Zurich, Switzerland
Michael Häusser, Wolfson Institute for Biomedical Research, University College London, UK
Andreas Herz, Bernstein Center for Computational Neuroscience Munich, Germany
Matthias Kaschube, Frankfurt Institute for Advanced studies, Germany
Simon Laughlin, University of Cambridge, UK
Máté Lengyel, University of Cambridge, UK 
Zhaoping Li,  University College London, UK
Jennifer Linden, UCL Ear Institute, UK
Thomas Mrsic-Flogel, Sainsbury Wellcome Centre, University College London, UK
Astrid Prinz, Emory University, USA
Maneesh Sahani, Gatsby Computational Neuroscience Unit, UCL, UK
Thanos Siapas, Caltech, USA
Tatjana Tchumatchenko, Max Planck Institute for Brain Research, Germany
Andreas Tolias, Baylor College of Medicine, USA
Byron Yu, Carnegie Mellon University, USA

This course is part of the CAJAL Advanced Neuroscience Training Programme - an initiative by FENS, IBRO and The Gatsby Foundation -, and is hosted at Champalimaud Foundation, Portugal. We are grateful to Google DeepMind for additional funding.
For more information on the CAJAL Training programme: www.cajal-training.org