Monday, June 2, 2014

[Comp-neuro] Real-life cognition contest (submission deadline Nov 1 2014)

In order to fully understand how the brain works, it is essential to
study the complex inter-play of cognitive processes that are
characteristic when interacting with a rich natural environment. Going
beyond the localization of individual aspects of brain function is
pivotal as there are clear limits to what we can learn about the
function of the brain as whole via restricting investigation to
specialized cognitive sub-systems in feature deprived laboratory

We believe that there is need for more publicly available data on
real-life cognition, as well as analysis strategies to study complex
concurrent neural processes. We invite research groups and individuals
to participate in a contest to master these challenges. As a starting
point, we have published a large dataset (functional MRI, simultaneous
cardiac and respiratory measurements, technical noise estimates,
high-res structural images (T1w, T2w, SWI, angiography, DTI), and
stimulus annotations) that is available to anyone without restrictions:

Hanke, M., Baumgartner, F.J., Ibe, P., Kaule, F.R., Pollmann, S., Speck,
O., Zinke, W. & Stadler, J. (2014). A high-resolution 7-Tesla fMRI
dataset from complex natural stimulation with an audio movie. Scientific
Data, 1. doi:10.1038/sdata.2014.3

Among all submissions that are received until November 1 2014 a jury
will determine the best contributions in terms of novelty of the
approach, scientific rigor, and potential impact on future research and
application. The best three contributions will receive an award (3000,
1500, and 500 Euro respectively) sponsored by the Center for Behavioral
Brain Sciences, Magdeburg, Germany.

The jury consists of:

Uri Hasson (Princeton University)
James Haxby (Dartmouth College)
Daniel Margulies (MPI Leipzig)
Russ Poldrack (U Texas, Austin)
Jean-Baptiste Poline (Neurospin)
Stefan Pollmann (CBBS, Magdeburg)
Peter Ramadge (Princeton University)

For more information, demos, and data access visit:

Comp-neuro mailing list

Sunday, June 1, 2014

[Comp-neuro] PhD Scholarship in Machine Learning for Neuroscience


The Department of Information Engineering and Computer Science (DISI) at the University of Trento and its research partner Fondazione Bruno Kessler (FBK), invites applications for 1 open PhD position covered by scholarship in the area of Machine Learning for Neuroscience.

The deadline for applications is June 16, 2014, before 16:00, CET.

The PhD research program aims at carrying out research activity on machine learning methodologies for neuroscientific data analysis. The main goal is the design and the deployment of machine learning algorithms for neuroimaging-based neuroscience investigations. The research focuses on three specific tasks: brain decoding, brain mapping and brain connectivity. The challenge is to design effective computational methods for multivariate pattern analysis.

The PhD research program will take place at NILab, the Neuroinformatics Laboratory raised as a joint initiative of the Bruno Kessler Foundation and the Center for Mind/Brain Sciences (CIMeC) of the University of Trento.

The University of Trento ranks 1st among the Italian Universities in the rankings of Times Higher Education and CIMeC ranks 1st for quality of research in the ranking of the Italian National for the Evaluation of Universities and Research (ANVUR). CIMeC has 6 ERC starting grants and 1 advanced grant. Trento ranks 1st in the annual survey on quality of life in Italian cities conducted by daily Il Sole 24 Ore.

Details on the PhD School and a link to the online application are provided below. For further information, please contact

- PhD School:
- FBK:
- NILab:
- CIMeC:

Comp-neuro mailing list

[Comp-neuro] Postdoc opening

Our Computational Neuroscience Lab at the Institute for Cognitive &
Neuroscience and Learning at the Beijing Normal University (BNU) has an
opening for a postdoc working in the field of computational
neuroscience. Our lab is interested in neural model building, neural information
processing, and data analysis in close collaboration with experimentalist in the
areas of neural correlates of perceptual learning in the visual cortex in
monkeys, multisensory integration, critical period plasticity in mice,
motion integration, group learning in fish, and others. We have very
close ties with a number of experimental groups on the campus, including
4 active awake monkey labs, eager to share data. There are thus various possible
research projects for a computational postdoc interested in data analysis and
model building in close collaboration with experiments.

We invite applications from prospective postdocs with background in a
computational discipline, such as computational neuroscience, computer
science, biophysics, computer vision, or machine learning. Former
experience working with neuroscience data is of advantage.

The position is open immediately and supported by the Chinese government
for 2 years and especially encourages non-Chinese applicants.
Eligible candidates must have a recent PhD from a renowned university,
strong publication record, fluent English proficiency and have to be
younger than 35. Salary is very competitive and adjusted to an
international level. Chinese knowledge is no requirement but willingness
to learn would help in daily life.

The Cognitive & Neuroscience and Learning Institute is a government
supported research facility with one of the strongest neuroscience
clusters in China. It is located within the urban center of the vibrant city
of Beijing with a multitude of attractions and active night life.

For more infos on research, see and (English site under construction).

If you are interested and qualified, please send a cover letter, CV,
transcripts of relevant publications to or


Dr. Malte Rasch
Associate Professor
Neural Data Modelling Group
State Key Lab for Cognitive Neuroscience & Learning
Beijing Normal University

Comp-neuro mailing list