We are happy to announce an opening for an internship position focused on the development of anonymization strategies for genetic data, with a specific emphasis on Genome-Wide Association Studies (GWAS) data. 

This internship position is part of a larger national project called CardI-HACK (Cardiogénomique des cardiomyopathies hypertrophiques héréditaires et stratification du risque en IA grâce à un challenge HACKathon), which aims to advance precision medicine by leveraging artificial intelligence (AI) to identify novel bioclinical scores for predicting the prognosis of Hypertrophic Cardiomyopathies (HCM), a group of hereditary heart diseases responsible for significant morbidity and mortality in young individuals.

 

Key Responsibilities

• Develop and implement anonymization strategies tailored for GWAS data. 
• Ensure that the anonymization process preserves the clinical significance of the data. 
• Balance the need for data privacy with the maintenance of its clinical utility.

 

Ideal Candidate

We are looking for an intern who:

• Has proven programming skills, particularly in data anonymization and analysis.
• Possesses strong analytical and problem-solving abilities.
• Demonstrates a commitment to handling sensitive data with the utmost integrity and confidentiality.
• Has knowledge in the fields of Genetics and Clinical Research (a plus but not required).
   

About the CardI-HACK Project

The CardI-HACK project aims to combine detailed genetic and clinical data and apply AI techniques to advance precision medicine. Specifically, the project seeks to identify new bioclinical scores that can better predict the prognosis of Hypertrophic Cardiomyopathies (HCM). HCM is a hereditary heart disease that often leads to sudden death or heart failure in individuals under 40 years of age.

During the hackathon, participants will work with genetic data sets and associated longitudinal follow-up data to identify combinations of rare and common genetic variants associated with severe forms of HCM. This includes the modeling of polygenic risk scores. Participants will also design and train algorithms to identify loci, genes, and variants significantly associated with disease progression, aiming to better understand the variable expression of the disease and identify new therapeutic strategies. This initiative also seeks to stimulate research into the underlying pathophysiology of HCM.

Interns will have access to an anonymized version of the genetic and bioclinical data from 150 representative patients in the training set at the beginning of the challenge, with access to anonymized data from an additional 250-350 patients later on.

About the IHU-ICAN

The IHU-ICAN (Foundation for Innovation in Cardiometabolism and Nutrition) brings together teams of fundamental and clinical researchers dedicated to cardiovascular, metabolic, and nutritional disease research. ICAN has developed cutting-edge technological platforms for translational research, including cardiovascular tissue imaging with France's first MRI dedicated to patient research and the exploitation of clinical databases with the European MAESTRIA project.

This internship offers a unique opportunity to work at the intersection of genetics, AI, and cardiology research in a dynamic and collaborative environment.

Application

To apply, please submit your resume and a cover letter outlining your qualifications and interest in this internship opportunity to 

m.ponnaiah@ihuican.org and baptiste.gregorutti@sorbonne-universite.fr