* Job *
We are looking for a research engineer with a background in Natural
Language Processing, Knowledge Representation and Semantic Web to join
the Inria WIMMICS team (http://wimmics.inria.fr). The context is the
ALOOF (Autonomous Learning of the Meaning of Objects,
https://project.inria.fr/aloof) CHIST-ERA European project. The goal of
the project is to enable robots and autonomous systems working with and
for humans to exploit the vast amount of knowledge on the Web in order
to learn about previously unseen objects. The system can then use this
knowledge when involved in human activities and acting in the real
world. More precisely, the project scenario consists of an open-ended
domestic setting where robots have to find objects.
Within this context, the goal of this engineering position is to go
beyond the current-state-of-the-art in knowledge acquisition for
cognitive systems by developing and combining techniques from text
mining to allow robots to engage in life-long learning from the Web.
Techniques that can harvest the Web to extract symbolic knowledge about
objects and their characteristics from unstructured text (relying on
natural language processing and machine reading techniques), as well as
available ontologies and knowledge on the Semantic Web will be
developed, grounding this knowledge in visual features so that robots
can recognize these objects in a real situation.
Given that the project is in its second year, we are ready to
consolidate and integrate the research work done so far into high
quality deliverables such as software and resources.
In particular, the following tasks will be addressed:
- Building a visual object category knowledge base and consolidate the
semantic object knowledge base created so far, relying on basic
ontological knowledge about objects extracted by analyzing unstructured
and structured information sources on the Web following the learning by
reading paradigm .
- Support the acquisition of semantic knowledge concerning object
properties and relations from the web [2,3].
- Cross-modal learning starting from labels of unconstrained data, to
efficiently acquire knowledge about an unknown object that has been
encountered in real time.
- Integration with the work from the other project partners, in
particular bridging the semantic and visual object knowledge extracted
from Web resources and the robot sensors.
Mandatory requirements for applicants:
1. PhD or MSc in Computer Science;
2. Experience in NLP, Knowledge Representation, Semantic Web, or in a
related field (Artificial Intelligence, Machine Learning...);
3. Hands-on experience of one or more of the following programming
languages (Python, Java) and technologies (XML, JSON, RDF/OWL, RESTful
Web services, *nix systems, scripting tools);
4. Fluent English is mandatory to work in an international team and to
exchange with the project European partners;
Project duration: 18 months
Deadline: open until filled
Working environment: the engineer will be employed at Inria Sophia
Antipolis, France, in the Wimmics team
Salary: Gross Salary per month according to the level of diploma and the
experience in the domain: 2500 – 2800€ / month (corresponding to
2100-2300€ net salary / month)
Contact email: Elena Cabrio: elena.cab...@unice.fr; Fabien Gandon:
 Valerio Basile, Elena Cabrio, Claudia Schon, KNEWS: Using Logical
and Lexical Semantics to Extract Knowledge from Natural Language, ECAI
2016 (poster paper).
 Valerio Basile, Elena Cabrio, Fabien Gandon, Building a General
Knowledge Base of Physical Objects for Robots, ESWC 2016 poster paper
 Jay Young, Valerio Basile, Lars Kunze, Elena Cabrio, Nick Hawes.
Towards Lifelong Object Learning by Integrating Situated Robot
Perception and Semantic Web Mining, ECAI 2016.
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