The WS-DIAMOND project is a European STREP project in FP6 including seven academic partners from Austria, France, Italy, and The Netherlands. It will start on September 1rst, 2005 for a period of 30 months.

The position
==========

The PhD position concerns the IASI (Artificial Intelligence and Inference Systems) research group of LRI-UMR 8623, the laboratory of Computer Science of the University Paris-Sud and CNRS, located at Orsay in the South of Paris. More information on the laboratory and the research team can be found by looking at http://www.lri.fr

The responsible of LRI inside this project is Prof. Philippe Dague, presently in position at LIPN-UMR 7030, the laboratory of Computer Science of the University Paris-Nord and CNRS, who will move to LRI on September 1, 2005.

The role of the IASI research group (in close collaboration with some researchers of LIPN and several of the partners) in the WS-DIAMOND project concerns more particularly:
- the development of formal models for Web services and diagnosability, and the way to acquire them in a (semi-)automatic way from existing information;
- the specification of model-based diagnosis and reconfiguration algorithms, adapted to distributed and adaptive networks,for composite and conversational Web services, and the prototyping of a surveillance platform;
- the definition of a new methodology for designing self-healing Web services and the prototyping of tools for checking diagnosability and repairability during design.

Priority, if needed, will be given during the thesis to the second topic.

Requirements
============

Candidates should have a good background in AI and knowledge of either model-based diagnosis or Web services technology. Additional experience with the design and implementation of distributed algorithms will be appreciated.

How to apply
============

- Send your application letter, including CV, academic results, and the names of referents, by email to Philippe.Dague@lipn.univ-paris13.fr
- For more information, please contact Philippe Dague.
- The salary is about 1800 Euros (gross/month).

Philippe Dague
LIPN-UMR 7030, Institut Galilée
Université Paris 13
99 avenue Jean-Baptiste Clément
93430 Villetaneuse, France
tel : (+33) 1 49 40 36 17
fax : (+33) 1 48 26 07 12
email : Philippe.Dague@lipn.univ-paris13.fr

==================================================================== Post-doc position on model-based monitoring and diagnosis of cooperative web services ===================================================================== We are looking for one post-doc (1 to 2 years) for the WS-DIAMOND (Web Services Diagnosability, Monitoring and Diagnosis) European project, which aims at designing self-healing Web services.

The WS-DIAMOND project is a European STREP project in FP6 including seven academic partners from Austria, France, Italy, and The Netherlands.

It will start on September 1rst, 2005 for a period of 30 months.

The position
==========

The post-doc position concerns the IASI (Artificial Intelligence and Inference Systems) research group of LRI-UMR 8623, the laboratory of Computer Science of the University Paris-Sud and CNRS, located at Orsay in the South of Paris. More information on the laboratory and the research team can be found by looking at http://www.lri.fr

The responsible of LRI inside this project is Prof. Philippe Dague, presently in position at LIPN-UMR 7030, the laboratory of Computer Science of the University Paris-Nord and CNRS, who will move to LRI on September 1, 2005.

The role of the IASI research group (in close collaboration with some researchers of LIPN and several of the partners) in the WS-DIAMOND project concerns more particularly: 1. the development of formal models for Web services and diagnosability, and the way to acquire them in a (semi-)automatic way from existing information;
2. the specification of model-based diagnosis and reconfiguration algorithms, adapted to distributed and adaptive networks,for composite and conversational Web services, and the prototyping of a surveillance platform;
3. the definition of a new methodology for designing self-healing Web services and the prototyping of tools for checking diagnosability and repairability during design.

The priority during the first 15 months will be on topics 1 and 2 and during the last 15 months on topics 2 and 3.

Requirements
============

Candidates should have:
- a (nearly) finished PhD thesis;
- good background in AI and good knowledge of model-based diagnosis and/or Web services technology;
- preferably, experience with the design and implementation of distributed algorithms.

How to apply
============
- Send your application letter, including CV, thesis reports, publications list and the names of referents, by email to Philippe.Dague@lipn.univ-paris13.fr
- For more information, please contact Philippe Dague.
- The salary is about 2200 Euros (gross/month).

Philippe Dague
LIPN-UMR 7030, Institut Galilée
Université Paris 13
99 avenue Jean-Baptiste Clément
93430 Villetaneuse, France
tel : (+33) 1 49 40 36 17
fax : (+33) 1 48 26 07 12
email : Philippe.Dague@lipn.univ-paris13.fr

Starting date : September 2005.

 Topic — It is commonly accepted that the requirements for diagnosis and reconfiguration should be considered at the earliest stages of design of a physical system. For this reason, methods for analysing the diagnosability of a system and determining which observables are needed to achieve the desired degree of diagnosability, are highly valued.
There has been a significant amount of work dealing with diagnosability and sensor placement in the AI Model Based Diagnosis community and methods have been proposed for :
• Assessing the level of discriminability of a system, i.e. given a set of observables, which faults can be discriminated? and its degree of diagnosability, i.e. the discriminability level related to the number of faults,
• Characterizing and determining the minimal set of observables that guarantee a specified diagnosability degree. This thesis aims at investigating how the approaches to design for diagnosability that have been proposed for physical systems can be adapted to the field of self-healing web services. Particular attention will be devoted to the issue of repairability and the design options that can be considered will be studied.Repairability will be supported by modeling the evolution and the composition of web services dynamic architecture and by contributing to define execution and coordination mechanisms.The aim is at producing a new design methodology and instruments for checking and ensuring such properties during design. This thesis is within the framework of the WS-DIAMOND (Web Services Diagnosability, Monitoring and Diagnosis) European project whose aim is to extend model-based technologies to deal with web services, both as regards diagnosis and repair during execution and as regards diagnosability and reconfigurabily during design.

Requirements — Candidates should have a good background in Computer Science and possibly AI and knowledge of either model-based diagnosis or web services technology. Additional experience with the design and implementation of distributed algorithms will be appreciated.

Contact — Louise Travé-Massuyès, +33 (0)5 61 33 63 02, louise@laas.fr

To apply — Send your application letter, including CV, two last years academic results, and the names of referents, by email to louise@laas.fr

You should have either an Undergraduate degree in Computing Science or a related discipline, and a PhD in a relevant AI/Cognitive Science sub-area or industrial experience is essential. For some of the projects experience with Applied Maths or Statistics would also be an advantage. For details see http://www.csd.abdn.ac.uk/research.

This post is available immediately until the end of September 2006 (in the first instance); it is anticipated that funding may be available to extend this post until September 2007. Informal enquiries can be made to: Professor Derek Sleeman, email dsleeman@csd.abdn.ac.uk or telephone +44 (0) 1224 272288 / 96.

Online application forms and further particulars are available from www.abdn.ac.uk/jobs. Alternatively email jobs@abdn.ac.uk or telephone (01224) 272727 (24-hour answering service) quoting reference number YCS015RX for an application pack.

The closing date for the receipt of applications is 8 September 2005.

The project investigates intelligent fault location in software and integrated software-hardware systems. The Research Fellow will work on in models and algorithms in the areas of model-based diagnosis, monitoring, and qualitative reasoning. Results will be incorporated in an existing diagnosis environment/interactive debugger.

Essential criteria include a PhD in Computer Science or related area, or equivalent accreditation and standing; background in Artificial Intelligence and knowledge/experience in one or several relevant areas such as knowledge representation, model-based or qualitative reasoning, or constraint technology. Experience with model-driven architecture or formal verification is advantageous.

To apply, send an application letter, including CV, publication list and the names of references by E-mail to Professor Markus Stumptner, at mst@cs.unisa.edu.au.

Position and lodgment details may also be obtained from http://www.unisa.edu.au/hrm/jobs/31Aug1.htm

The University is an Equal Opportunity Employer and reserves the right to consider late applications until the position is filled, to invite applications, or not to make an appointment.