[robotics-worldwide] [jobs] Four PostDoc Positions Available at the Center for Applied Autonomous Sensor Systems, Sweden

Marcello Cirillo marcello.cirillo at oru.se
Thu Dec 4 02:09:08 PST 2014

             ***** Four PostDoc Positions Available *****

          Center for Applied Autonomous Sensor Systems (AASS)
                      Örebro University, Sweden

In Short

Applications are invited for four PostDoc positions at Örebro University,
Sweden.  All positions are funded by the National project "Semantic Robots".

We seek applicants in one or more of the following areas:
-- Long term 3D mapping and localization
-- Vision based mapping and localization
-- Semantic perception and semantic object perception

About the Semantic Robots Project

The overall aim of the project is to develop Semantic Robots, that is,
robots which use multi-semantic models of their environment, tailored to
their action and perception capabilities, in order to automatically derive
and execute action plans that achieve given goals.

The project will integrate research in robotics and artificial intelligence
to address closely related topics, namely, semantics-based perception, 3D
world modelling and planning for long-term operation in dynamic
environments. Semantic perception provides human-like meaning to the
information a robot acquires about its environment: it derives symbolic
representations from sensor data and uses them for reasoning.  Models of
the robot's environment should go beyond current 3D metric and topological
maps, as they should be able to store and maintain more than just geometric
information over long periods of time. The information extracted from the
models could then be used for planning at different levels of abstraction,
from task planning to fleet motion coordination.

The Semantic Robots project involves Örebro University as the academic
partner and a number of Swedish industrial partners, including Volvo
Construction Equipment, AtlasCopco and Kollmorgen Automation. The overall
aim is twofold: to advance the state of the art in key areas of robotics
and artificial intelligence, and to demonstrate the results obtained in
industrially relevant settings.

About the Positions

The successful candidate will be employed as a PostDoc with Örebro
University for an expected duration of 2 years.

The main task of the PostDocs will be to perform world-class research on
one or more of the areas below. Background/expertise in combinations of
these areas is a plus.

-- Long term 3D mapping and localization in large scale dynamic environments

The research in this area will focus on building consistent 3D maps of
large environments. This involves working with cutting edge 3D scanning
technology applied to autonomous industrial vehicles operating in
real-world settings. More specifically, the work will address the
development of new algorithms to deal with varying scales of dynamics in
the environment, so as to maintain accurate models over long periods of
time. In addition, research in this area will also focus on extracting and
maintaining relevant semantic information (e.g., terrain classification,
lane extraction, traffic flow information) from the model of the
environment. The work will be carried out in close cooperation with several
industrial partners, over different application scenarios.  Additional
opportunities for work on computer vision based methods and camera based
modelling and localization are also within the scope of this area. The
successful candidate will have prior experience in mapping, SLAM and 3D
scan registration. Experience with vision-based mapping and localization is
a plus.

-- Vision based mapping and localization in natural environments

The work in this area will focus on using and developing novel camera
techniques for mapping and localization in large, real-world environments,
ranging from large gardens to indoor warehouses. Research in this area will
concentrate on using machine learning and data mining techniques for
developing new ways of representing additional semantic information into
maps. For instance, part of the effort will be to include into maps
information about different types of vegetation in outdoor environments and
loading/storage areas or pedestrian crossings within warehouses. Also, the
work will encompass camera based modeling, detection and tracking of
people. Although the main focus of this area lies with using camera-based
sensors, it will be possible to work also with other sensor modalities,
such as LIDAR, laser or RGBD. The work in this area will be carried out in
close cooperation with several industrial partners.  The successful
candidate will have prior experience in the areas of machine learning,
computer vision and mapping.

-- Semantic perception

Semantic perception is a central component to enable higher level reasoning
and planning in robotic systems. An important part of semantic perception
involves naming objects and measured phenomena in the environment and
understanding the relations between them. This also entails providing an
intuitive description of the environment in term of semantics that can be
effectively shared with human users. The successful candidate will have
experience in semantic perception for robotics involving both multi-modal
perception, and applications in indoor and outdoor environments. The
candidate is expected to hold a PhD degree in the domain of machine
learning, computer vision, or robotics. Excellent skills in software
development are required. Experience with working with industry is a plus.

Successful candidates will work in close cooperation with a core group of
senior researchers and PhD students at AASS who specialize in knowledge
representation and reasoning, perception and mapping and planning for
robots.  The results obtained within the scope of Semantic Robots are
expected to be demonstrated outside lab test conditions in
industrially-relevant scenarios and to be published in top-ranking
conferences and journals. A small amount of teaching may also be part of
the PostDoc's duties.

Prerequisites and Application Process

In addition to a clear interest, the successful applicant must have a solid
theoretical background and working experience in one or more of the above
research topics. A PhD degree in computer science, robotics or comparable
field is required, as well as a strong publication record in relevant
topics. Knowledge of the Swedish language is not required, but proficiency
in both written and spoken English is mandatory.

To apply for a position, please send to <sr-recruitment at aass.oru.se>:
+ A motivation letter
+ An updated CV (including at least two references)
+ Copies of 2/3 most relevant publications
+ Copy of PhD thesis (if available)
+ An updated publication list (and, preferably, a link to the applicant's
Google Scholar profile)

Applications can be sent immediately, and they will be accepted until the
positions are filled.  We are looking forward to receiving your application!

About the Place

Örebro University (www.oru.se) is a young university which currently
enrolls more than 15,000 students.  It is located in Örebro, a city of
130,000 inhabitants situated in central Sweden.

The Center for Applied Autonomous Sensor Systems (AASS) is one of the
Strong Research Environments at Örebro University.  It carries out
multi-disciplinary research at the intersection of robotics, machine
learning, artificial intelligence, computer vision, computer science, and
measurement technology. The research and human environment at AASS is young
and enthusiastic. Researchers come from a dozen different countries, in
Europe and worldwide, and have different scientific and cultural
backgrounds.  AASS also frequently hosts international researchers and is
involved in several international projects.

AASS is internationally renowned for its research in mobile robotics,
cognitive robotic systems, robot ecologies, and artificial olfaction.
Further information can be found at www.aass.oru.se/Research/Robots/ and

Marcello Cirillo , Ph.D.
AASS Research Center
Department of Technology, Örebro university (Sweden)
Email: marcello.cirillo at aass.oru.se

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