Idiap has a new opening for an Internship in genomics and health informatics

A 6-months paid internship is available in the group of Genomics and Health Informatics at the Idiap Research Institute in Martigny. This 6-month project is suitable as an external MS project.

The project

Background Amyotrophic Lateral Sclerosis (ALS) is a rapidly progressive and incurable neurodegenerative disease. The early events underlying the disease remain poorly understood. As a dramatic consequence no effective treatment has been developed. We previously found that the molecular events leading to ALS start during early development [1, 2]. It remains however unknown how and when these affect individual cell behaviour.

Goal Time-lapse fluorescence live-cell imaging are rich data that can be used to detect and track individual cell's changes (size, morphology, movement) in space and time. The goal of the project is to develop an image analysis pipeline to extract and analyse single-cell phenotypic measurements from large-scale time-lapse fluorescence imaging data. Specifically it will involve:

  1. expansion on existing image analysis modules to obtain robust single-cell readouts from longitudinal images obtained from RFP labelling;
  2. development of statistical models to identify cellular trajectories associated with early stage of ALS development using the phenotypic features.

Framework This project is part of a larger one aiming to study how molecular biology shapes cellular morphology at early stage of ALS by integrating longitudinal cellular imaging with genomic data. It involves a close collaboration with the experimental laboratories of professor Rickie Patani (Stem Cell Research laboratory, Francis Crick Institute/ UCL, London ) and Andrea Serio (Neural Circuit Bioengineering group,Kings College, London).

Our research group

The Genomics and Health Informatics group has recently been launched at Idiap to complement Idiap's research activities and expertise with genomics and bioinformatics. The research group develops computational methods to analyse and integrate large-scale data such as genomics, imaging and digital data to improve the understanding of the molecular biology behind neurodegenerative disorders, and also to identify disease biomarkers that assist in early detection of the disorders and in personalizing the treatment.

The candidate

Candidates should have a Bachelor or Master degree (or in its final year) in an area relevant for the project and strong mathematical and computational skills. Candidates should be familiar with Python, R, and with the Linux environment. Experience in next-generation sequencing data, machine learning and image processing is an asset. Candidates do not necessarily have to have a biological background but should have a strong desire to directly work with experimental biologists. The candidates should have a good knowledge of English.

Prospective candidates should apply through the Idiap Online Recruitment System (ORS) only. Inquiries about the position can be addressed to Dr. Raphaëlle Luisier ( ). Review of applications will begin immediately and proceed until the position has been filled.