on performance) postdoc position in self-organizing systems is
available at the Laboratory of Excellence (LABEX) at the Université de
Technologie de Compiègne (UTC) in France (www.utc.fr/labexms2t).
The successful candidate will work with Dr. Eliseo Ferrante on
exciting topics at the interface between self-organized artificial
life, robotics systems and statistical physics. The Postdoc position
is expected to start in Fall 2016 or later (flexible) and is open
until filled.
Project description:
Our lab considers self-organizing systems from a unique
interdisciplinary point of view that combines artificial life,
engineering, statistical physics, and biology. We study how various
biological and technological components can collectively achieve
complex dynamics using only simple rules and no centralized control.
Examples include bird flocks, insect and robot swarms, and bacteria
colonies coordinating to achieve collective motion.
One of the fundamental challenges of self-organizing systems is the
integration of local and global dynamics. While individual components
are mainly linked to local sensing and actuation, coherent global
responses are required for the organism or group to perform and
survive collectively. In order to achieve this collective response,
those systems need to have correlations in at least some of their
individual state variables that scale up with the system's size.
Various processes may provide mechanisms for this coherent collective
response. For example, the addition of few long-range interactions is
enough to produce integrated dynamics in small-world networks.
Furthermore, in absence of long-range interactions, systems in a
critical state (between order and disorder) naturally display
long-range correlations that can achieve coherent system-level
dynamics. Finally, there could also be other types of interaction
modes responsible for reaching coherent collective response.
The project undertaken by the candidate will be focused on
understanding self-organizing system that must simultaneously manage
local and organism-level dynamics. The candidate will study systems in
which a collective response is generated at the collective scale, as a
function of stimuli that are exerted at the local scale. The candidate
will explore whether this property is already present in existing
self-organization mechanisms, and potentially develop novel models in
which collective response is generated by the interplay between three
different mechanisms: small-world topologies, criticality, and
self-organization. Potential applications include collective
exploration and surveillance with technological devices such as
drones, which will take advantage of this collective response in order
to have a fast reaction to a discovered resource.
The candidate will be using tools such as multi-agent simulations and
mathematical models to study collective systems with different types
of interaction patterns. She or he will focus on scenarios where
global and local dynamics needs to be integrated in a group of agents,
in order to achieve specific collective goals involving collective
response, such as: mapping an unknown environment, achieving
collective response to the discovery of a feature in the environment,
performing dynamic agent re-allocation in the environment, etc … In
order to do so, the candidate will focus on analyzing the interplay
between the different mechanisms able to achieve collective response,
in order to find which configuration is best for each scenario.
Candidate's profile:
The candidate must have earned a Doctorate degree in computer science,
statistical physics, complex systems, or relevant disciplines, and
must be self-motivated and able to work autonomously.
The candidate is expected to be proficient in programming languages
such as Python, Java, C++ and to have solid knowledge of scientific
software packages such as Matlab, R, Mathematica. The candidates must
have experience with large-scale multi-agent simulations, and
familiarity with mathematical modeling of collective systems using
several techniques (ODEs, mean field approximations, chemical reaction
networks, Fokker-Planck equations, Langevin equations, etc …) will
definitely be a plus.
Candidates with an interdisciplinary background that are interested in
questions at the interface between science and engineering will be
highly preferred.
Fluent English (written and spoken) is required, and only applications
in English will be accepted. Above all, the applicants must be
motivated, autonomous, and able to learn quickly and work effectively
on challenging research problems.
Documents required to apply:
To apply, you can send the following documents to Eliseo.Ferrante@hds.utc.fr:
- Curriculum vitae
- At least two references and/or recommendation letters
- A statement of research experience and interests
- Publication record stating impact factor (if present) and number of citations
For any informal enquiry about the eligibility conditions, as well as
for more details about the position, please contact Eliseo Ferrante
<eliseo.ferrante@hds.utc.fr>.
--
Eliseo Ferrante, PhD
Labex MS2T Junior Research Chair
Joint Laboratory HEUDIASYC
Labex MS2T
UMR CNRS 7253
Université de Technologie de Compiègne (France)
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