plunkett@daimi.dk (Kim Plunkett) (04/27/89)
The Institute of Psychology, University of Aarhus, Denmark is announcing a new position at the Associate Professor level. Applicants should document research within the area of psychology or Cognitive Science which involves the relation between information and computer technology, and psychological processes. Qualifications within the latter area - the relation to computer technology and psychology - will be given special consideration. For further details, please contact Dr. Kim Plunkett: psykimp@dkarh02.bitnet (Deadline for receipt of applications: June 2nd, 1989)
gac@cs.brown.edu (Glenn Carroll) (02/28/91)
I'm forwarding the following notice for an available position.
PLEASE NOTE THE RETURN ADDRESS.
From: CSA::GYULASSY 21-FEB-1991 08:32:48.00
To: CARROLL
CC: GYULASSY
Subj: net jon
Research Position Available Effective March 1,1990
Place: Nuclear Science Division
Lawrence Berkeley Laboratory
Area: Neural Network Computing Research with Application to
Complex Pattern Recognition Problems
in High Energy and Nuclear Physics
Description:
Experiments in high energy and nuclear physics are confronted with
increasingly difficult pattern recognition problems, for example in tracking
charged particles and identifying jets in very high multiplicity and noisy
environments. In 1990, a generic R&D program was initiated at LBL to develop
new computational strategies to solve such problems. The emphasis is on
developing and testing artificial neural network algorithms. Last year we
developed a new Elastic Network type tracking algorithm that is able to track
at densities an order of magnitude higher than conventional Road Finding
algorithms and even Hopfield Net type algorithms.
This year we plan on a number of followup studies and extensions of that work
as well as begin research on jet finding algorithm. Jets are formed through the
fragmentation of high energy quarks and gluons, via a rare process in high
energy collisions of hadrons or nuclei. The problem of identifying such jets
via calorimetric or tracking detectors is greatly complicated by the very high
multiplicity of fragments produced via other processes. The research will
involve developing new preprocessing strategies and network architectures to be
trained by simulated Monte Carlo data.
Required Qualifications: General understanding of basic neural computing
algorithms such as multilayer feed forward and recurrent nets and a variety of
training algorithms. Proficiency in programing in Fortran and C on a variety of
systems VAX/VMS and/or Sparc/UNIX.
Interested applicants should contact Miklos Gyulassy
Mailstop 70A-3307
LBL
Berkeley, CA 94720
E-mail: GYULASSY@LBL.Bitnet
Telephone: (415) 486-5239
arpanet: gac@cs.brown.edu
bitnet: gac@browncs.bitnet
csnet: gac%cs.brown.edu@relay.cs.net
tenet: all of us are equal, but some are more equal than others.