The Machine Learning for Integrative Genomics team 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 available immediately and will remain open until filled. The position is initially for 12 months with the possibility of extension. Salary is commensurate with experience according to Institut Pasteur guidelines.
Application :
Send CV, motivation letter, and contacts details of 2-3 references to laura.cantini@pasteur.fr
For more information : https://research.pasteur.fr/en/team/machine-learning-for-integrative-genomics/