About the role
The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning methods for single-cell data analysis (tools developed by the team: https://github.com/cantinilab).
Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating exciting opportunities for machine learning to address outstanding biological questions. The postdoc to be recruited will be working on the development of machine learning methods for single-cell data and will require interactions with collaborators of the team.
Required skills
We expect a candidate with a strong background in machine learning or statistics. The candidate must also be proficient in high-level languages like Python. Familiarity with single-cell date and experience with existing single-cell methods and software would represent a strong advantage. Excellent communication skills and team spirit, and an ability to work in autonomy are essential. Fluent English both spoken and written is required
The candidat must have a PhD in computer science, machine learning, or computational biology
The position is initially for 12 months with the possibility of extension.
Application : send CV, motivation letter, and contacts details of 2-3 references to laura[dot]cantini[at]pasteur.fr
For more information : https://research.pasteur.fr/en/team/machine-learning-for-integrative-genomics/