IICCSSS 2019 is over!

A big thank you to everyone involved ūüôā Stay tuned for IICCSSS 2020!

Announcement:

The International Interdisciplinary Computational Cognitive Science¬†Spring School (IICCSSS) is an annual educational meeting for students and young researchers interested in computational approaches to brain and cognitive sciences. Its first iteration will take place in the period of March 25th ‚Äď 31st, 2019 at the Bernstein Center Freiburg, Germany.

Application is closed (all applicants should have received a notice about the outcome of their application. Please get in touch if you haven’t heard back).

Please note that there is limited capacity for the event. You will hear about the outcome of your application latest by the end of February. Please note that due to visa application constraints, the FENS/IBRO-PERC stipend deadline has passed already.

List of speakers:

  • Radoslaw Martin Cichy (Free University Berlin)
  • Frank J√§kel¬†(Technische Universit√§t Darmstadt)
  • Falk Lieder (MPI Intelligent Systems, T√ľbingen)
  • Peggy Series (University of Edinburgh)
  • Lilian Weber (ETH Zurich)
  • Arvind Kumar (KTH Stockholm)
  • Jose Guzman (IMBA Vienna)
  • Timo Flesch (University of Oxford)
  • Philipp Hummel (Universit√§t T√ľbingen)
  • Benedikt Ehinger (Radboud University, Nijmegen)
  • Michael Tangermann (Brain State Decoding Lab, Freiburg)
  • Stefan Rotter (Bernstein Center Freiburg)
  • Tonio Ball (Neuromedical AI Lab, Freiburg)
  • Pierre LeVan (Universit√§tsklinikum Freiburg)
  • Sebastian Spreitzer (Bernstein Center Freiburg)
  • Ulrich Egert (Bernstein Center Freiburg)

Financial support for international students:

FENS and IBRO-PERC provide 4 stipends of 750 EUR for master or PhD students interested in attending this course.
 
Through these stipends FENS and IBRO-PERC aim to encourage and promote international experience of students; hence, students that are currently residing or studying in the Germany are not eligible for a FENS and IBRO-PERC stipend for this course.
 
‚ÄúTrue intuitive expertise is learned from prolonged experience with good feedback on mistakes.‚ÄĚ
Quote by Daniel Kahneman