Received: from GLINDA.OZ.CS.CMU.EDU by A.GP.CS.CMU.EDU id aa03087; 7 Aug 95 18:53:12 EDT Received: from GLINDA.OZ.CS.CMU.EDU by GLINDA.OZ.CS.CMU.EDU id aa13498; 7 Aug 95 18:52:45 EDT To: ai+ai-postdoc@cs.cmu.edu Subject: Postdoc: Neural Networks/Fuzzy Logic at Univ. of Southampton (UK) Date: Mon, 07 Aug 95 18:52:34 -0400 Message-ID: <13496.807835954@GLINDA.OZ.CS.CMU.EDU> From: Mark Kantrowitz Sender: ai@A.GP.CS.CMU.EDU From: Martin Brown Subject: 2 postdoctoral positions available Date: 24 Jul 1995 14:54:47 GMT Organization: Electronics and Computer Science, University of Southampton UNIVERSITY OF SOUTHAMPTON DEPARTMENT OF ELECTRONICS AND COMPUTER SCIENCE RESEARCH FELLOWS Two postdoctoral positions are currently available on an EPSRC grant entitled Neurofuzzy Construction Algorithms and their Application in Non-Stationary Environments. Links to the groups, personnel and industrial companies can be obtained from the project's homepage at: http://www-isis.ecs.soton.ac.uk/research/projects/osiris.html Two postdoctoral researchers are required to investigate the development and application of advanced network construction algorithms and training rules for neurofuzzy systems operating in a time-varying environment. The candidates should possess skills in applied mathematics and computer science and have experience in such areas as numerical analysis, Visual C++ programming, neural/fuzzy learning theory, dynamical systems and optimisation theory. This research will be undertaken in association with Neural Computer Sciences http://www.demon.co.uk/skylake/ who produce an object oriented, 32 bit MS windows-based neural networks package called NeuFrame and benchmarking data sets will be collected from GEC and Lucas. In addition, Eurotherm controls are supplying tools to investigate the possibility of developing embedded devices. Post One - One researcher is required for 3 years to investigate and further develop the neurofuzzy construction algorithms that have been proposed by the ISIS group. They will be based at Southampton under the supervision of Martin Brown and Chris Harris. The neural+fuzzy approach allows vague, expert knowledge to be combined with numerical data to produce systems that make the best use of both information sources. However, for ill-defined, high-dimensional systems it would be useful to configure a network's structural parameters directly from the data. Recent research has shown that B-spline-based neurofuzzy systems are suitable for use in such algorithms due to their direct fuzzy interpretation, numerical conditioning and ease of implementation, and by considering an ANalysis Of VAriance (ANOVA) representation, the B-spline neurofuzzy networks can be shown to overcome the curse of dimensionality for many practical problems. A good background in numerical analysis and modelling theory (additive, neural/fuzzy) is required, and as the algorithms will be developed within a Visual C++, Microsoft Foundation Classes environment, hence knowledge about these products would also be useful. Informal enquiries for this post should be made to Dr Martin Brown in the ISIS research group, Department of Electronics and Computer Science, University of Southampton, UK (Tel +44 (0)1703 594984, Email: mqb@ecs.soton.ac.uk). Salary will be in the range of 15,986 - 18,985 per annum. Applicants for post one should send a full curriculum vitae (3 copies from UK applicants and 1 from overseas), including the names and addresses of three referees to the Personnel Department (R), University of Southampton, Highfield, Southampton, SO17 1BJ, telephone number (01703 592750) by no later than 25 August 1995. Please quote reference number R/553. Post Two - A second researcher is required for 2 years (with the possibility of it being extended for an extra year) to investigate on-line learning for non-stationary data. They will be based at Brighton University under the supervi sion of Steve Ellacott. This work will investigate several aspects of training neurofuzzy systems on-line such as: * learning algorithms for large, redundant training sets * recurrent training rules * high-order instantaneous learning algorithms * aspects of data excitation and on-line regularisation The ideal candidate would be a mathematician or mathematically oriented engineer with a background in numerical analysis and/or dynamical systems. Familiarity with neural network algorithms would be an advantage, but is not essential. The post will involve some programming in C or C++. All enquiries and applications for post two should be made to Dr Steve Ellacott in the Department of Mathematical Sciences, University of Brighton, UK (Tel +44 (0)1273 642544, Email: s.w.ellacott@brighton.ac.uk). working for equal opportunities a centre of excellence for university research and teaching ------------------------------------------------------------------------------- This message | Submissions ai+ai-postdoc@cs.cmu.edu was sent via | Subscribe/Unsubscribe ai+query@cs.cmu.edu the AI-POSTDOC | Available mailing lists include mailing list. | AI-JOBS, LISP-JOBS, PROLOG-JOBS, AI-POSTDOC, AI-PREDOC