PhD-Approche frugale Sémantique Formelle pour comprendre des conversations

Orange SA; Lannion; On-site; USD 35,010 - 58,350; Full time

Job summary

Ein innovatives Unternehmen sucht einen leidenschaftlichen Forscher für eine Doktorarbeit im Bereich der formalen Semantik für das Verständnis von Gesprächen. Diese spannende Rolle bietet die Möglichkeit, an der Schnittstelle von Linguistik und Informatik zu arbeiten, indem man formale Ansätze zur Analyse von Gesprächen anwendet und innovative Sprachmodelle entwickelt. Die Herausforderungen umfassen das Verständnis von Dialogsequenzen und die Verwaltung von Turn-Taking. Wenn Sie ein tiefes Interesse an Sprache und ihren Strukturen haben und bereit sind, an vorderster Front der Forschung zu arbeiten, könnte dies die perfekte Gelegenheit für Sie sein.

Qualifications

• Kenntnisse in Linguistik und formaler Semantik sind erforderlich.
• Erfahrung mit Deep Learning und Sprachmodellen ist gewünscht.

Responsibilities

• Durchführung einer Doktorarbeit zur formalen Semantik für das Verständnis von Gesprächen.
• Entwicklung von Sprachmodellen und Evaluierungskorpora.

Skills

Linguistik

Formale Semantik

Graphentheorie

Deep Learning

Sprachmodelle

Education

Master in NLP/Computational Linguistics/Computer Science

Tools

Python

Pytorch

Linux

LaTeX

Job description

about the role

Your role is to conduct a PhD thesis on: "Approach in Formal Semantics for Conversation Understanding."

Global Context and Problematic of the Subject
In NLP, there is a representation of the meaning of sentences in the form of a graph (Abstract Meaning Representation, AMR) that allows for the handling of various application tasks using small language models (< 1B, such as FlanT5 with between 256M and 1.2B parameters). For dialogue, this representation is not yet utilized, except for robot commands.

Scientific Objective – Results and Challenges to Overcome
By illustrating the connection with the global context and the problematic, the thesis aims to directly describe what it addresses: "The objective of the thesis is to..."
The objective of the thesis is to adapt generic approaches of formal semantic analysis to conversation understanding. In addition to not requiring specific training for each application, their advantage is their low computational resource requirements.

The main challenges to overcome (scientific or technical) are:

• Understanding the sequence of exchanges (dialogues)
• Managing turn-taking
• Resolving coreferences

Among the recommended approaches to overcome these challenges are:

• Using formal semantics in the form of directed graphs
• Machine Learning / Deep Learning
• Manipulating semantic graphs

Finally, the main expected outcomes (besides publications and manuscript writing) are:

• Trained language models and tools for dialogue
• Evaluation corpus
• Evaluation

about you

We are looking for a person who is interested in language, its structures, and its ambiguities:

Required Skills (scientific and technical) and Personal Qualities for the Position

• Knowledge in linguistics, particularly formal semantics
• Understanding of graph theory
• Experience with deep learning and language models
• Development tools:
  • Python, Pytorch
  • Linux
  • LaTeX

Required Education

• completed Master in NLP/Computational Linguistics/Computer Science

Desired Experience

• Internships involving linguistic data and language structures