Ph.D. - Explainable Artificial Intelligence and therapeutic target identification


Oncodesign SA and the Distributed Artificial Intelligence and Knowledge laboratory (CIAD LAB – UMR 7533) at the University of Bourgogne Franche-Comte have a vacancy for a Ph.D. fellowship.


About the position 


Biological networks are very effective tools for modeling, analyzing, and discovering new biological interactions in complex biological systems. 

In recent years, network models and algorithms have been used for the development of precision medicine for many diseases. 

The mathematical machinery at the heart of this research field is based on graph theory, a widely studied disciplinary field. 

This is also associated with machine learning on structured data in the form of graphs. 

A big challenge is to create better modeling tools to integrate human expertise and artificial intelligence techniques to exploit big data for clinical research and drug development,  to advance a better understanding of health and disease and formulate a hypothesis on a new mechanism of actions and identify corresponding innovative therapeutic targets. . To meet this challenge, many emerging works propose the design of explainable AIs, allowing the identification of innovative therapeutic targets. These explainable AIs combine connectionist AI approaches such as deep learning, neural networks, etc., and causal AIs based on modeling causal graphs of knowledge derived from the knowledge of domain experts. 


This research will address questions such as:


-  How to aggregate data sources from heterogeneous biological and medical databases while maintaining the consistency of the associated knowledge?

-  What are the best functions for analyzing raw data to extract knowledge?

-  How to develop in silico prediction of new therapeutic targets which will then be validated in vitro and/or in vivo? 


Required selection criteria


The qualification requirement is that you have completed a master’s degree with a strong academic background in one or more of biology, computer science, and engineering, mathematics, or equivalent education with a grade of the first third of the promotion. 

The candidate must have a background in computer science with ideally skills in machine learning and/or knowledge engineering. 

Knowledge in the field of biology will be required.

Applicants must provide evidence of good English language skills, written and spoken. Mastery of the French language will be appreciated.


Preferred selection criteria

-  Background in Artificial Intelligence and/or Data Mining/Data Science applied in medicine and  biology

-  A candidate with some industrial experience in the aforementioned areas will get preference.

-  Publication activities in the aforementioned disciplines will be considered an advantage.


Salary and conditions


Ph.D. candidates are remunerated by the company. The amount of the salary can be negotiated with the company. 

The appointment is for a term of 3 years and can be extended beyond the Ph.D. defense.

Appointment to a Ph.D. position requires that you are admitted to the Ph.D. program in computer science and that you participate in an organized Ph.D. program during the employment period.


About the application


This research is funded by the French government and the Oncodesign SA ( in the frame of CIFRE Ph.D. (Conventions Industrielle de Formation par la Recherche). 

Oncodesign and the CIAD laboratory have initiated a scientific collaboration in the field of precision medicine. 

This collaboration concerns the identification of new therapeutic targets and the acceleration of the research and development phases of new molecules. 

The job will be located at Dijon, a gastronomic and touristic French city at 1.5 hours from Paris by train. 

The CIAD Lab and Oncodesign are 500 meters distance.


Application deadline: 31.06.2021