PostDoc with expertise in Computational Biology/Bioinformatics

Location: France
Application Deadline: Open until filled
Published: 2 months ago

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We are looking for a computational biologist/bioinformatician at the postdoc/research assistant level to join the ERC Synergy project DecoLeishRN (https://cordis.europa.eu/project/id/101071613).

The successful candidate will join and collaborate with a vibrant, international team that applies experimental evolution to study mechanisms of fitness gain in the eukaryotic pathogen Leishmania.

The candidate will apply and develop computational tools for the analysis of large data sets generated by short-read, long-read, and single cell DNAseq/RNAseq analyses of cells evolving in vitro in culture and in vivo in infected animals. The major aim of his/her project is to understand how Leishmania can harness its intrinsic genome instability for the evolution of beneficial phenotypes.

The position is immediately available and can be considered as a springboard to independence.

The Institut Pasteur in Paris has multiple state of-the-art facilities and constitutes a vibrant research community with 13 Departments across the Biology/Physics/Biomedical fields.

In particular, the fellow will benefit from an exceptional computational infrastructure at the Institut Pasteur BioHub (75 bioinformatics engineers) and at the Weizmann Institute of Sciences interacting with our partner team of Prof Yitzhak Pilpel.

Interested candidates should send a motivation letter, CV (including 3 names for references) and list of publications to gerald.spaeth@pasteur.fr. This call will be open until a suitable candidate has been recruited.

Relevant literature

Bussotti G et al., PNAS 2023, https://pubmed.ncbi.nlm.nih.gov/36848551/

Piel L et al., PLoS Pathog. 2022, https://pubmed.ncbi.nlm.nih.gov/35294501/

Späth GF and Bussotti G, NAR 2022, https://pubmed.ncbi.nlm.nih.gov/34928370/

Bussotti G et al., PNAS 2021, https://pubmed.ncbi.nlm.nih.gov/34903666/

Prieto Barja P et al., Nat Ecol Evol. 2017, https://pubmed.ncbi.nlm.nih.gov/29109466/

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