Received: from GLINDA.OZ.CS.CMU.EDU by A.GP.CS.CMU.EDU id aa09699; 21 Jun 95 14:53:29 EDT Date: Wed, 21 Jun 95 14:50:14 EDT From: AI.Repository@GLINDA.OZ.CS.CMU.EDU To: ai+ai-predoc@cs.cmu.edu Subject: Research Studentships: Aston University, UK Sender: ai@A.GP.CS.CMU.EDU From: listerrj@aston.ac.uk (RJ LISTER) Subject: PhD Research Studentships Date: Wed, 7 Jun 1995 12:19:00 GMT Neural Computing Research Group ------------------------------- Dept of Computer Science and Applied Mathematics Aston University, Birmingham, UK PHD RESEARCH STUDENTSHIPS ------------------------- *** Full details at http://neural-server.aston.ac.uk/ *** The Neural Computing Research Group has attracted substantial levels of industrial and research council funding and will therefore be able to offer a number of full-time PhD studentships to commence in October 1995. Currently we are seeking candidates for four studentships. These will pay full fees at the home rates and hence are suitable for UK and European Union citizens only. The studentships also cover living expenses at the same rate as a research council studentship. Feature Extraction Techniques for Nonstationary Financial Market Time Series ---------------------------------------------------------------------------- The project will examine conventional and neural network techniques for the extraction of features to elucidate hidden structure in generally multivariate financial time series.The problem domain is made more complicated by the inherent nonstationarity of the time series. Techniques based on dynamical systems theory and statistical pattern analysis will be developed and applied to real-world data. The ideal candidate should be mathematically and computationally competent and have a general interest in the field of financial mathematics, although no previous experience in this area is required. The project is in collaboration with a financial company, Union CAL Ltd, London. Validation and Verification of Neural Network Systems ----------------------------------------------------- (Two Studentships) One of the major factors limiting the widespread exploitation of neural networks has been the perceived difficulty of ensuring that a trained network will continue to perform satisfactorily when installed in an operational system. In the case of safety-critical systems it is clearly vital that a high degree of overall system integrity be achieved. However, almost all potential applications of neural networks entail some level of undesirable consequence if the network generates incorrect or inaccurate predictions. Currently there is no general framework for assessing the robustness of neural network solutions or of systems containing embedded neural networks. These two studentships will be closely associated with a substantial project funded by the Engineering and Physical Sciences Research Council to address the basic issues involved in validation of systems containing neural networks. The studentships are funded by two industrial companies: British Aerospace and Lloyds Register of Shipping, and will involve developing case studies to demonstrate the applicability of validation and verification techiques to real-world applications involving neural networks. Potential candidates should be mathematically and computationally competent with a background either in artificial neural networks or another relevant field. Neural networks applied to ignition timing and automatic calibration -------------------------------------------------------------------- This project involves a collaborative research programme between the Neural Computing Research Group and SAGEM in the general area of applying neural networks to the ignition timing and calibration of gasoline internal combustion engines. The ideal student would be computationally literate (preferably in C/C++) on UNIX and PC systems and have good mathematical and/or engineering abilities. An awareness of the importance of applying advanced technology and implementing ideas as engineering products is essential. In addition the ideal candidate would have some knowledge and interest in internal combustion engines and also relevant sensor technology. Neural Computing Research Group ------------------------------- The Neural Computing Research Group currently comprises the following academic staff: Chris Bishop Professor David Lowe Professor David Bounds Professor Geoffrey Hinton Visiting Professor Richard Rohwer Lecturer Alan Harget Lecturer Ian Nabney Lecturer David Saad Lecturer (arrives 1 August) two further posts (currently being appointed) together with the following Research Fellows: Chris Williams Shane Murnion Alan McLachlan Huaihu Zhu four further posts (currently being advertised) a full-time software support assistant, and eleven postgraduate research students. How to Apply ------------ If you wish to be considered for one of these positions you will need to complete an application form which can be obtained by sending your full postal address to: Professor C M Bishop Research Admissions Tutor Neural Computing Research Group Department of Computer Science and Applied Mathematics Aston University Birmingham B4 7ET, U.K. Tel: 0121 359 3611 ext. 4270 Fax: 0121 333 6215 e-mail: c.m.bishop@aston.ac.uk The minimum entry qualification is a First Class or Upper Second Class Honours degree in a relevant discipline, or the equivalent overseas qualification. Overseas applicants whose first language is not English must provide evidence of competence in English. Acceptable evidence includes possession of a UK or North American degree, or a formal certificate such as the British Council's ELTS (6.0 or better) or the USA TOEFL (550 or better). ------------------------------------------------------------------------------- This message | Submissions ai+ai-predoc@cs.cmu.edu was sent via | Subscribe/Unsubscribe ai+query@cs.cmu.edu the AI-PREDOC | Available mailing lists include mailing list. | AI-JOBS, LISP-JOBS, PROLOG-JOBS, AI-POSTDOC, AI-PREDOC