Connectionists: postdoc position with Jon Roiser at UCL
Peter Dayan
dayan at gatsby.ucl.ac.uk
Mon Nov 18 11:25:31 EST 2013
A post-doctoral research associate position in computational psychiatry
is available in the laboratory of Dr Jonathan Roiser at the UCL Institute
of Cognitive Neuroscience. See
http://www.icn.ucl.ac.uk/Vacancies/index.html for further
details.
Deadline 12th December 2013.
JOB DESCRIPTION
Post-doctoral research associate (Salary £32,375 to £39,132 including
London Allowance)
Main Purpose
The post-holder will be expected to carry out research in the area of
cognitive neuroscience, including neuroimaging and computational
modelling. The post-holder will be responsible for the design and
conduct of behavioural, functional neuroimaging and other cognitive
neuroscience experiments with humans (including depressed individuals),
recording and analysing data and preparing the results for publication.
Summary of Duties and Responsibilities
To design, set up and conduct experiments in consultation with
the Principal Investigator, ensuring the acquisition of good quality
data, including the recruitment and testing of participants
To oversee the work of a post-graduate research assistant
To record, analyse and write up the results of experiments,
maintaining a permanent record of the methodologies and the experiment
To prepare and present findings of research activity to
colleagues
To contribute to the writing, submission and revision of papers
to be submitted to appropriate peer reviewed journals, collaborating
with others as appropriate
SUMMARY OF PERSONAL SPECIFICATION
PhD (in the process of submission) in computational neuroscience
or mathematical psychology; or PhD (in the process of submission) in
neuroscience/cognitive neuroscience with considerable experience
applying computational modelling techniques to data
Extensive experience using Matlab, R or comparable software
packages
Considerable knowledge of data analysis using computational
modelling and associated literature
Good knowledge of cognitive neuroscience findings in the field
of reinforcement learning
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