Connectionists: Postdoctoral Position in France

Tue Sep 27 13:05:40 EDT 2005

Dear all,

Please circulate to interested parties. Please DO NOT RESPOND 
DIRECTLY TO ME.  send replies and queries to Robert French at the 
address below.

Best regards,

Denis Mareschal

==================
Two year Post-doctoral position available:
Neural Network and Genetic Algorithm Models of Category Learning

We have obtained funding from the European Commission for a two-year 
post-doctoral position to study the mechanisms underlying the 
emergence of rule-based category learning in humans.  The project is 
a highly interdisciplinary effort by researchers from Birkbeck 
College of the University of London, the University of Amsterdam, the 
University of Burgundy in Dijon, and Exeter and Cardiff Universities 
in the UK.  The research will include ERP studies, experimental work 
with animals, experimental work  with infants, children, and adults, 
as well as computational modelling. At the heart of this project is 
the need to develop connectionist (neural network) models of category 
learning that capture the developmental transitions observed both in 
infants across developmental time, as well as  in different species 
across evolutionary time.
The post-doctoral fellow will work primarily with Professor Robert 
French, a specialist in the area of neural network research, at the 
Learning and Development Laboratory (LEAD-CNRS) at the University of 
Burgundy in Dijon, France. There will be opportunities for close 
collaborations with the Centre for Brain and Cognitive Development, 
Birkbeck University of London.
Interested candidates should contact Professor French at 
robert.french at u-bourgogne.fr. 

Professor Robert M. French:  French is currently a research director 
for the French National Scientific Research Center (CNRS).  He has 
worked closely with the co-ordinator of the FAR project, Denis 
Mareschal at Birkbeck College in London for the past decade.  He is a 
highly interdisciplinary computer scientist who specialises in 
connectionist modelling of behaviour. In addition to having a PhD in 
computer science from the University of Michigan under Douglas 
Hofstadter and John Holland, he has formal training in mathematics, 
psychology and philosophy. He has published work ranging from 
foundational issues in cognitive modelling, models of bilingual 
memory, catastrophic interference in neural networks and artificial 
life. He has published in many of the areas directly related to the 
goals of this grant - namely, evolution, computational evolution, 
artificial neural networks, and infant categorisation. 

Computational skills: The simulations will be written in Matlab, and, 
while it is not necessary to know Matlab from the outset, excellent 
programming skills in some common programming language are necessary 
(e.g., C++, Java, Pascal, Lisp, etc.).  Knowledge, and preferably 
practical experience of genetic algorithms and neural networks is 
important.  A familiarity with some of the basic techniques of 
experimental psychology (especially category learning) and basic 
statistics (e.g., ANOVA, t-test, non-parametric tests, regression and 
correlation) will also be a plus.

Language skills: Must have excellent standards of academic writing in 
English, and good oral communication skills.  French is not required.

Dijon:  Dijon is an hour an a half by train southwest of Paris, 
located in the heart of France's famous Burgundy wine region and is 
one of the gastronomic centers of France.  It is a beautiful city 
with a long history as the capital of Burgundy. The old town has been 
beautifully preserved.  It has a very active cultural life, boasting 
arguably the finest music auditorium in France.  The gently rolling 
hills of the region are ideal for hiking and biking. Dijon is home to 
the University of Burgundy, with approximately 20,000 students.  The 
relative proximity of Paris (1:39 by train, one train an hour) makes 
for easy day-trips there for concerts, expositions, or tourism.

LEAD: The successful candidate will be housed within LEAD 
(Experimental Laboratory for Learning and Development).  This is one 
of the leading experimental psychology labs in France, carrying the 
prestigious CNRS label given to a select few labs in France and based 
on the publication record of the lab members and their international 
impact.  They are especially strong in the areas of implicit 
learning, music cognition and modeling.  To find out more about this 
lab, see: http://www.u-bourgogne.fr/LEAD

Salary:  The before-tax salary will be between 24,000 and 30,000 
euros depending on the past experience of the candidate. (A typical 
pre-tax salary of 26,800 euros would mean an after-tax yearly salary 
of 21,960 euros.) Additional funding will be provided for computer 
equipment and travel to conferences and workshops.  Standard social 
benefits available to employees of the University of Burgundy are 
provided.

Responsibilities: The emphasis will be on research, publication and 
presentation of the FAR work at international venues. The successful 
candidate will be expected to develop (in collaboration with 
Professor French and other members of the project), implement and 
test connectionist models of category learning consistent with the 
objectives of the project.

Duration of contract:  The contract is to begin no later than January 
1st, 2006 and is of a fixed term 2-year duration.

Please send a CV, including references who may be contacted, to:
robert.french at u-bourgogne.fr  

The position will be kept open until a suitable candidate is 
appointed. We anticipate having a first round of interviews at the 
end of October.

The European Commission encourages woman and minority candidates to 
apply for positions funded by them. 

Further Details of Overall Project

 From Associations to Rules (FAR): Project summary

Human adults appear different from other animals by their ability to 
use language to communicate, their use of logic and mathematics to 
reason, and their ability to abstract relations that go beyond 
perceptual similarity. These aspects of human cognition have one 
important thing in common: they are all thought to be based on rules. 
This apparent uniqueness of human adult cognition leads to an 
immediate puzzle: WHEN and HOW does this rule-based system come into 
being? Perhaps there is, in fact, continuity between the cognitive 
processes of non-linguistic species and pre-linguistic children on 
the one hand, and human adults on the other hand. Perhaps, this 
transition is simply a mirage that arises from the fact that Language 
and Formal Reasoning are usually described by reference to systems 
based on rules (e.g., grammar or syllogisms).
	To overcome this problem, we propose to study the transition 
from associative to rule-based cognition within the domain of concept 
learning. Concepts are the primary cognitive means by which we 
organise things in the world. Any species that lacked this ability 
would quickly become extinct (Ashby & Lee, 1993). Conversely, 
differences in the way that concepts are formed may go a long way in 
explaining the greater evolutionary success that some species have 
had over others.
	To address these issues, this project brings together 5 teams 
of leading international researchers from 4 different countries, with 
combined and convergent experience in Animal Cognition and 
Evolutionary Theory, Infant and Child Development, Adult Concept 
Learning, Neuroimaging, Social Psychology, Neural Network Modelling, 
and Statistical Modelling.

Project objectives

This project has six key objectives designed to understand how 
learning and development interact in the emergence of rule-based 
concept learning. To this end, we have identified 6 specific 
objectives:

1. To develop a computational (mechanistic) model of the emergence of 
rule-based concept learning both within the individual and across 
evolution.
2. To establish statistical tools for discriminating rigorously 
between rule-based and similarity-based classification behaviours.
3. To establish the conditions under which human adults show 
rule-based or similarity-based concept learning.
4. To chart the emergence across species of similarity vs. rule-based 
concept learning.
5. To chart the emergence of rule-based concept learning in human 
infants and adults.
6. To chart the emerging neural basis of rule-based concept learning 
and human adults, children, and infants.

-- 
=================================================

	Dr. Denis Mareschal
	Centre for Brain and Cognitive Development
	School of Psychology
	Birkbeck College
	University of London
	Malet St., London
	WC1E 7HX, UK
	tel +44 (0)20 7631-6582/6226 reception: 6207
	fax +44 (0)20 7631-6312
	http://www.psyc.bbk.ac.uk/people/academic/mareschal_d/

=================================================