post doc position, modified job description

Kai Goebel (goebel@pawn.Berkeley.EDU)
Wed, 29 May 1996 17:12:01 +0200


Job Description:
Define and develop advanced monitoring and diagnostic techniques for
application in the Intelligent Vehicle Highway System (IVHS) paradigm.
Develop a module, "Intelligent Decision Advisor" for detecting hazards. This
involves: developing tools and techniques within this module for optimal
remedial action in the presence of hazards and developing models for optimal
decision making under uncertainty in real-time. Model the process as an expected
value decision problem and investigate the suitability of various optimization
and soft computing techniques. Document results through technical reports,
publications, and software to be implemented on a real system.

Availability: Immediately

Time Duration: 1 Year

Background:
A Ph.D. in either Mechanical Engineering, Electrical Engineering,
Computer Science, or Industrial Engineering is required. An ideal
candidate would have a background in decision analysis, probabilistic
modeling, and optimization. Additional background in fuzzy logic, machine
learning, controls, and sensor technology is desirable. Experience in
application of these theories to complex mechanical applications is
also desirable.

Contact:
Professor Alice Agogino
aagogino@euler.me.berkeley.edu