Mots-Clés
artificial intelligence
integrative analysis
single-cell
scRNA-seq
scATAC-seq
spatial transcriptomics
Description
Role :
The Machine Learning for Integrative Genomics team, led by Laura Cantini, is recruiting a permanent research engineer. The successful candidate will carry out single-cell data analysis in the context of collaborations with wet-lab biologists, both on campus and with external partners. The role will primarily involve applying tools developed within the team, as well as standard single-cell analysis methods. In addition, the candidate will be responsible for the long-term maintenance of the team’s GitHub repositories and for addressing issues related to the tools developed by the team. If collaborations allow, time and support for an additional personal research project aligned with the team’s research will be encouraged.
Environment :
The Machine Learning for Integrative Genomics team, led by Laura Cantini, develops artificial intelligence tools for the integrative analysis of multiple single-cell data modalities, including scRNA-seq, scATAC-seq, and spatial transcriptomics. The team is part of the Department of Computational Biology and also holds a secondary affiliation with the Development Department, as well as an affiliation with CNRS. The recruited candidate will be affiliated 80% with Laura Cantini’s team and 20% with the Bioinformatics and Biostatistics HUB.
Information about the teams :
The Machine Learning for Integrative Genomics team : https://research.pasteur.fr/en/team/machine-learning-for-integrative-genomics/
The HUB : https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/
Degree :
PhD in computer science, computational biology, bioinformatics or similar
Relevant skills :
Hard skills :
Python programming
familiarity with the fundamentals of machine learning and interest on methodological aspects
fluent English both spoken and written is required
prior experience with bulk and/or single-cell data analysis tools is a plus
previous experience in the management of collaboration with wet-lab biologists will be a plus
Soft skills:
team spirit
ease in communication
multitasking
problem-solving ability and effective time management
ability to work in autonomy on different projects