Lab: EURECOM, Data Science Department Supervisor: RaphaŽl 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 at eurecom.fr with the reference: DS_RT_PhD_SILKNOW_2018
-- RaphaŽl Troncy EURECOM, Campus SophiaTech Data Science Department 450 route des Chappes, 06410 Biot, France. e-mail: raphael.troncy at eurecom.fr & raphael.troncy at gmail.com Tel: +33 (0)4 - 9300 8242 Fax: +33 (0)4 - 9000 8200 Web: http://www.eurecom.fr/~troncy/