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Laboratoire/Entreprise : Télécom SudParis / Aldebaran
Durée : 36 mois
Contact : Amel.Bouzeghoub@telecom-sudparis.eu
Date limite de publication : 2023-07-07

Contexte :
This thesis is a CIFRE and a collaboration between Telecom SudParis and Aldebaran. The position will start in October 2023.

Keywords: Knowledge Graphs, Graph Database, Medical Ontology, Medical History taking

Sujet :
The aim of this PhD thesis is to build a graph-oriented data lake to store all patient health data connected to a relevant medical ontology. Patient data are acquired through Aldebaran (https://aldebaran.care/) digital medical history-taking device that generates a medical report for generalist practitioners. The logic of medical history-taking is supported by a knowledge graph database comprising up to 600 questions, 3000 responses, and 6000 relationships. As of April 1st 2023, 2500 questionnaires and their medical reports have been generated. Of note, each response
of a patient to a question generates lexical annotations for the medical reports and semantic annotations supported by Conceptual Graphs (CG). CGs are the basis of the hyper-contextuality of the medical history tracking device. As it supports the semantics of the response, it will also populate the patient data graph. The main objectives of this thesis project are threefold : (i) to propose a model for patients’ reported health needs, characteristics, and continuum of
care using knowledge graphs and including existing standards (OMOP, OHDSI, HL7-FIHR) in a future perspective of interoperability and data analysis ; (ii) to provide a safe and efficient mean to enrich the patient file with longitudinal data acquired along successive medical consultations. In this respect, temporality management is a key challenge ; (iii) to propose a method to ensure the contextualization and conciseness of the questionnaire according to the elements already known in the patient data graph.

Profil du candidat :
For this thesis, we will consider candidates with a Master’s or Engineer ‘s degree with knowledge about several of the following skills:

– Fluent in written and spoken English. Some knowledge of French can be useful.
– Skills in mathematics (statistics, graphs) and computer science (algorithms, machine learning, knowledge, data modeling, symbolic artificial intelligence, Natural Language Processing)
– Mastery of Python language, Cypher, (React), and experience in software development
– Adaptability and ability to invest in the field of medical application
– Experience in a research laboratory

This thesis is a CIFRE and a collaboration between Telecom SudParis and Aldebaran. The position will start in October 2023.

Formation et compétences requises :
Master’s or engineer’s degree in Computer Science with an affinity for Machine Learning.

Adresse d’emploi :
The PhD student will be co-hosted by Telecom SudParis (Palaiseau site) and Aldebaran (Paris).

Applications should be submitted by email to Amel.Bouzeghoub@telecom-sudparis.eu, Julien.Romero@telecom-sudparis.eu, and christian@aldebaran.care

They must include the following:
– A Curriculum Vitae;
– Transcripts of records of undergraduate and graduate studies;
– Link to MSc thesis and publications if applicable;
– Link to personal software repositories
– Name of 2 or 3 references to contact (position, email);