[agents] Postdoctoral Research Position on "Operational Research and Artificial Intelligence for self-adaptation of systems in dynamic environment"

[Emmanuel ADAM]

/[Apologies if you receive multiple copies of this message]/

The Université Polytechnique Hauts-de-France (UPHF) offers a Post-Doc 
position in OR/AI

We are looking for candidates who have skills in OR and AI for a 
post-doc position that will start in March 2020.
The deadline for proposal is January 3, 2020

/See below for a detailed description./

Feel free to share this position proposal with your network,

Best regards,
Emmanuel Adam

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*Title:* /Operational Research and Artificial Intelligence for 
self-adaptation of systems in dynamic environment/
*Hosting organization: */LAMIH (UMR CNRS 8201) - UPHF (Université 
Polytechnique Hauts-de-France)/
*Contact Person:* /E. Adam (emmanuel.adam at uphf.fr), A. Ait El Cadi 
(abdessamad.AitElCadi at uphf.fr)/
*Duration:* /24 months/
*Application deadline:* /January 3th , 2020 /

*Research profile:* Researcher with a recent doctorate in one of the 
fields: operational research, artificial intelligence. A 
multidisciplinary experience in these two areas would be an advantage.
*Mobility:* Occasional journeys abroad (CIRRELT, Canada) are to be expected.

*Project & Institute background :*
The Université Polytechnique Hauts-de-France (UPHF) with the LAMIH UMR 
CNRS 8201 (Laboratory of Industrial and Human Automation control, 
Mechanical engineering and Computer Science) offer a post-doc position 
within the International Associated Laboratory LIA-ROI-TML ("Operational 
Research and Computer Science in Transport, Mobility and Logistics") 
between LAMIH and CIRRELT (Interuniversity Research Center on Enterprise 
Networks, Logistics, and Transport).
The researcher will work, with an internationally recognized team, on 
subjects resulting from the collaboration between the two laboratories, 
in France and Canada. He / she will also benefit from the large 
experience of the researchers involved in the ELSAT2020 project 
(Ecomobility, Logistics, Security and Adaptability in Transport), a 
project in which LAMIH, the host laboratory, is actively involved.

*Position summary:*
The research aims at the integration of Operational Research and 
Artificial Intelligence approaches in order to offer new methods, more 
effective and more resilient, adapted to the new challenges of the OR 
approaches. Indeed, the complexity of the encountered problems, in both 
laboratories, makes the use of OR or AI separately often limited. Thus, 
classical OR methods reach limits, that some AI methods can help to 
overstep. The joint contribution of these two approaches in guiding the 
search for solutions and adapting to changing contexts is more than 
promising.
The research project intends to develop and evaluate artificial 
intelligence systems capable of self-adaptation in order to refine 
solutions obtained from operational research algorithms. The OR-AI 
relationship will lead to models at the interface of both approaches.
The missions will, therefore, mainly tend to combine OR and AI in order 
to provide innovative solutions for  problems under study in our 
research areas, and namely in the LIA's topic: Transport, mobility, and 
safe and sustainable intelligent urban systems.

*Example of applications :*
Thus, you may be invited to join the research on subjects in the 
following themes :
/_Adaptation and evaluation :_/ on the basis on activities planning, 
tasks scheduling, resources sharing, computed with exact or heuristic 
methods, the objectives are: to allow local adaptation to unforeseen 
events, like disruptions, context changes, using technics from 
distributed intelligence (agents, …); to contribute to the proposal, 
validation and analysis of metrics, which allow measuring the efficiency 
of adaptive approaches when compared to classical ones.
/_Guidance :_/ to resolve a problem, the guidance of the meta-heuristic 
depends on its nature, its context. These two factors are not fully 
known a priori but discovered along the resolution. In order to 
‘speed-up’ the resolution in the intensification-diversification cycles, 
the use of optimization technics, based on learning mechanisms and/or 
decentralized AI methods could be studied.

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