PhD proposal (H2020 project): "Knowledge Modeling and Multilingual Information Extraction for Understanding the Silk Cultural Heritage"

Understanding the Silk Cultural Heritage"

Lab: EURECOM, Data Science Department
Supervisor: Raphaël Troncy
Project context: H2020 SLKNOW project, http://silknow.eu/
Financial support: European Commission, H2020 program
Start date: asap
Duration: 3 years
Link (EN): 
http://www.eurecom.fr/sites/www.eurecom.fr/files/jobs/DS_RT_PhD_SILKNOW_juilllet_2018_US.pdf
Link (FR): 
http://www.eurecom.fr/sites/www.eurecom.fr/files/jobs/DS_RT_PhD_SILKNOW_juilllet_2018_FR.pdf 


Context:
The overall objective of this PhD thesis is to develop novel methods and 
tools for semantically modeling, annotating and visualizing museum 
records. To this aim, an improved scientific understanding on 
multilingual text analysis, enrichment and visualization will be 
developed. This PhD program addresses more specifically the following 
topics:
* Model the SILKNOW ontology for describing silk textiles, their 
historic evolution and their relations with society by extending the 
CIDOC-CRM ontology. Develop converter tools that generate knowledge 
graphs for cultural heritage.
* Build an intelligent system to automatically extract meaning 
(semantics) and relate data from separate collections, by means of data 
processing and deep learning techniques. The considered data will be 
heterogeneous (regarding to the various ways of discretizing and storing 
data), multilingual (English, Spanish, French and Italian) and 
multimodal (text, videos and images of different nature). The emphasis 
will be on a text analytics module that will generic semantic 
annotations of records
* Evaluate information extraction methods on a wide range of use cases 
and international benchmarks
* Develop advanced end-user applications enabling to visualize and 
interact with semantically enriched metadata collection including an 
Web-based exploratory search engines but also other type of natural 
interfaces (e.g chatbot)

This PhD position is funded as part of the SILKNOW H2020 European 
Project that aims to improve the understanding, conservation and 
dissemination of European silk heritage from the 15th to the 19th 
century. It applies next-generation computing research to the needs of 
diverse users (museums, education, tourism, creative industries, 
media…), and preserves the tangible and intangible heritage associated 
with silk. Based on records from existing catalogues, it aims to produce 
digital modelling of weaving techniques (a “Virtual Loom”), through 
automatic visual recognition, advanced spatio-temporal visualization, 
multilingual and semantically enriched access to digital data.

Requirements:
* Education Level / Degree: MSc (with distinction)
* Field / specialty: Computer Science, Data Science, Web Science, 
Computational Linguistics, Artificial Intelligence
* Technologies: Ontology Engineering, Natural Language Processing, 
Knowledge Base population, Semantic Web, Machine Learning, AI
* Languages / systems: English (French and Spanish is a plus)
* Other skills / specialties: Web development technologies, UI/UX

Application:
The position is available immediately and application evaluation will be 
continuous until the position is filled. Interested candidates should 
submit (I, II and III):
* I-Curriculum Vitae
* II-Motivation letter of two pages also presenting the perspectives of 
research and education
* III-Names and addresses of three references
Applications should be submitted by e-mail to raphael.troncy@eurecom.fr 
with the reference: DS_RT_PhD_SILKNOW_2018

-- 
Raphaël Troncy
EURECOM, Campus SophiaTech
Data Science Department
450 route des Chappes, 06410 Biot, France.
e-mail: raphael.troncy@eurecom.fr & raphael.troncy@gmail.com
Tel: +33 (0)4 - 9300 8242
Fax: +33 (0)4 - 9000 8200
Web: http://www.eurecom.fr/~troncy/

Received on Tuesday, 2 October 2018 08:23:58 UTC