Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!usc!jarthur!uunet!brunix!gac
From: gac@cs.brown.edu (Glenn Carroll)
Newsgroups: comp.ai.neural-nets
Subject: position available
Message-ID: <66525@brunix.UUCP>
Date: 27 Feb 91 19:23:27 GMT
Sender: news@brunix.UUCP
Reply-To: GYULASSY@LBL.Bitnet
Organization: Brown University Department of Computer Science
Lines: 61

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

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