PIPGEN - PhD Project 15: Improving accuracy and time-to-diagnosis of rare disease by developing AI-based algorithms.
Research · qGenomics (qG) > Spain
RESEARCH PROFILE: First Stage Researcher (R1)
APPLICATION DEADLINE: 27 June 2021
EU RESEARCH FRAMEWORK PROGRAME: HORIZON 2020
MARIE SKOLODOWSKA CURIE GRANT AGREEMENT NUMBER: 955534
 First Stage Researcher (R1) PhD candidate or equivalent. Early stage researcher with less than 4 years FTE research experience.
PhD Project details
Next generation sequencing technologies have accomplished the long-awaited milestone of sequencing a genome at a cost below $1000. This makes it possible that millions of people affected by rare diseases can benefit from a diagnostic genetic test. However, once genome or exome sequence is produced, variant annotation, prioritisation and ultimately interpretation in the clinical and familial context, still remains the most important and costly bottleneck. ESR15 will develop a software that incorporates Artificial Intelligence algorithms at different steps and facilitates data interpretation, so at the end, the procedure is faster, more robust, and reliable. ESR15 will develop different machine learning algorithms to improve the process key steps: 1) automation of clinical history gathering into HPO terms, 2) variant categorisation according to ACMG classification, 3) prioritisation of disease-causing mutations, in the scope of the informed phenotype and variants identified.
Host: qGenomics (qG), Spain.
Supervisor: Dr. Lluis Armengol.
Envisioned secondments: U-Paris, Amstersdam UMC.