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Reference : UMR7357-MARURB-004
Workplace : STRASBOURG
Date of publication : Monday, June 29, 2020
Scientific Responsible name : Olivier POCH, Pierre COLLET
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2020
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly
Description of the thesis topic
The aim of the thesis is to develop explicable AI approaches for the integrated classification and prediction of rare genetic diseases, more specifically congenital myopathies (CM). The early differential diagnosis of the different CMs is a major challenge and could be greatly enhanced by combining clinical (symptoms), genetic/genomic (sequences) and histological (images/reports) data from the MyoCapture reference cohort of 1200 individuals whose data set has recently been integrated in the INEX-MED knowledge base. In this framework, we propose to learn from the INEX-MED database to develop an explainable predictive model, MYO-xIA, based on the Behavioral Anticipatory Classifier System (BACS) coupled with deep neural networks. MYO-xIA will be dedicated to the differential diagnosis of CMs on the basis of the patient's symptoms, in order to guide genetic/genomic analyses and/or complementary clinical/histological explorations that are often invasive and costly, thus improving patient management.
The thesis project is the winner of the CNRS call for projects 80 Prime, and will be done in collaboration between INS2I and INSB. The PhD will take place at ICube (Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie), Strasbourg in the CSTB (Complex Systems and Translational Bioinformatics) team. The project is multidisciplinary and involves Jocelyn Laporte's team at the IGBMC, Strasbourg for the genetic and diagnostic aspects.
Constraints and risks
The successful candidate shall be enrolled on a PhD program at Strasbourg University, doctoral school MSII or SVS.
The candidate should hold a Master2 degree in Bioinformatics. The position requires expertise in programming, algorithms and databases, combined with strong knowledge of genetics, molecular and cellular biology and understanding of research experiences in genomic data analysis. Good oral and written communication skills (French and English required) would be appreciated for presenting at conferences and writing articles in scientific journals. A good mastery of the French language will be essential for the project because many interactions with the French biomedical community (doctors, associations, patients, etc.) are planned. In view of the highly interdisciplinary aspect of the research to be carried out, the doctoral student will have to demonstrate a great openness of mind and an ability to interact effectively with collaborators from different disciplines (computer scientists, biologists, clinicians). We are looking for a young researcher who will know how to get involved in his project, curious, with a certain autonomy and a strong motivation to develop AI skills in the biomedical field.
Applications should include a detailed CV; at least two references (who may be contacted); a one-page cover letter; a one-page summary of the master's thesis; the grades of the Master2).
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