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<p><font size="-2"><i>[Apologies if you receive multiple copies of
this message]</i></font></p>
The Université Polytechnique Hauts-de-France (UPHF) offers a
Post-Doc position in OR/AI
<p>We are looking for candidates who have skills in OR and AI for a
post-doc position that will start in March 2020.<br>
The deadline for proposal is January 3, 2020</p>
<p><i>See below for a detailed description.</i></p>
<p>Feel free to share this position proposal with your network,<br>
</p>
Best regards,<br>
Emmanuel Adam<br>
<p>--------</p>
<p><b>Title:</b> <i>Operational Research and Artificial
Intelligence for self-adaptation of systems in dynamic
environment</i><br>
<b>Hosting organization: </b><i>LAMIH (UMR CNRS 8201) - UPHF
(Université Polytechnique Hauts-de-France)</i><br>
<b>Contact Person:</b> <i>E. Adam (<a
class="moz-txt-link-abbreviated"
href="mailto:emmanuel.adam@uphf.fr" moz-do-not-send="true">emmanuel.adam@uphf.fr</a>),
A. Ait El Cadi (<a class="moz-txt-link-abbreviated"
href="mailto:abdessamad.AitElCadi@uphf.fr"
moz-do-not-send="true">abdessamad.AitElCadi@uphf.fr</a>)</i><br>
<b>Duration:</b> <i>24 months</i><br>
<b>Application deadline:</b> <i>January 3th , 2020 </i><br>
<br>
<b>Research profile:</b> 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.<br>
<b>Mobility:</b> Occasional journeys abroad (CIRRELT, Canada) are
to be expected.<br>
<br>
<b>Project & Institute background :</b><br>
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).<br>
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.<br>
<br>
<b>Position summary:</b><br>
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.<br>
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.<br>
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. <br>
<br>
<b>Example of applications :</b><br>
Thus, you may be invited to join the research on subjects in the
following themes :<br>
<i><u>Adaptation and evaluation :</u></i> 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.<br>
<i><u>Guidance :</u></i> 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.<br>
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