post-doc position in Montreal / machine learning + bootstrap for database mining

[Yoshua Bengio]

POST DOCTORAL RESEARCH STAFF MEMBER IN
STATISTICAL DATA ANALYSIS AND MACHINE LEARNING
FOR HIGH-DIMENSIONAL DATA SETS

MATHEMATICS OF INFORMATION TECHNOLOGY AND COMPLEX SYSTEMS
(MITACS: a new Canadian Network of Centers of Excellence)

Position to be held jointly at the Department of Computer Science & 
Operations Research and the Department of Mathematics and 
Statistics, at the UNIVERSITY OF MONTREAL, Quebec, Canada


NATURE AND SCOPE OF THE POSITION:

A post-doctoral position position is available at the University of
Montreal within the MITACS network of centers of excellence. The position
is subject to the approval of funding by the MITACS Board of Directors. 
The  main research area will be the statistical data analysis of
high-dimensional data sets with machine learning algorithms, also
known as, "database mining". The main research questions that will be 
addressed in this research are the following:
 - how to deal with the "curse of dimensionality": algorithms
   based on variable selection or based on combining many variables
   with different importance, while controlling generalization to avoid 
   overfitting;
 - how to make inferences on the models obtained with such methods,
   mostly using resampling methods such as the BOOTSTRAP.
This research will be performed within the MITACS project entitled
"INFERENCE FROM HIGH-DIMENSIONAL DATA". See
 http://www.iro.umontreal.ca/~bengioy/mitacs.html
for more information on the project and
 http://www.mitacs.math.ca
for more information on the MITACS network.
The candidate will be working under the supervision of professors
Yoshua Bengio (computer science and operations research) and
Christian Leger (mathematics and statistics). See 
 http://www.iro.umontreal.ca/~bengioy 
and
 http://www.iro.umontreal.ca/~lisa
for more information respectively on Yoshua Bengio and his 
laboratory. See
 http://www.dms.umontreal.ca/~leger
for more information on Christian Leger. 


ESSENTIAL SKILLS, KNOWLEDGE, AND ABILITIES:

Candidates must possess a recent Ph.D. in computer science,
statistics, mathematics, or a related discipline, with
a research background in machine learning (in particular
neural networks) and/or computational statistical methods
such as the bootstrap. Candidates must have excellent
programming skills, with demonstrated experience.

Experience in the following areas will be mostly considered:

- Statistical data analysis in general,
- bootstrapping methods in particular.
- Machine learning algorithms in general,
- artificial neural networks in particular.
- Programming skills in general,
- object-oriented programming,
- participation in large-scale, multiple authors, software projects,
- experience with C, C++ and S-Plus languages, in particular.


LENGTH OF EMPLOYMENT: 1 year (with possible
renewal for 4 years total), starting as soon
as possible.

FOR FURTHER INFORMATION, PLEASE CONTACT:

Yoshua Bengio 
 bengioy at iro.umontreal.ca, 
 514-343-6804, fax 514-343-5834
or
Christian Leger 
 leger at dms.umontreal.ca
 514-343-7824, fax 514-343-5700

Electronic applications (preferably as a postscript, raw text, or pdf
file) are encouraged, in the form of a a Curriculum Vitae with
information on academic experience, academic standing, research
experience, programming experience, and any other relevant
information (e.g., pointer to your web site, if any).

-- 
Yoshua Bengio 
Professeur aggrégé
Département d'Informatique et Recherche Operationnelle
Université de Montréal, C.P. 6128 Succ. Centre-Ville,
2920 Chemin de la Tour, Montreal, Quebec, Canada H3C 3J7
Tel: 514-343-6804. Fax: 514-343-5834. Bureau 3339.
http://www.iro.umontreal.ca/~bengioy
http://www.iro.umontreal.ca/labs/neuro