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.
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.
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 candidate must have a PhD in computer science, machine learning, or computational biology.