The Life Sciences Department at the BSC integrates the independent research of senior scientists that work on various aspects of computational biology, ranging from bioinformatics for genomics to computational biochemistry and text mining. The Computational Biology group (http://cgenomics.org), which is jointly affiliated with the Institute for Research in Biomedicine (IRB), is involved in multiple projects covering a wide range of topics, including evolutionary and comparative genomics, phylogenomics, and metagenomics. One of the central projects of the group is funded through a Moore-Simons Foundation project (LECA-TIME) and is focused on understanding the timing and modularity in the acquisition of genes in the Last Eucaryotic Common Ancestor (see Pittis and Gabaldón 2016, Vosseberg et al. 2020). In this context, we are looking for a motivated postdoc with expertise in phylogenetics and evolutionary biology to work on phylogenomic projects to faithfully reconstruct the evolutionary history of thousands of gene families to discover ancient trends in gene family evolution. The candidate will collaborate with other researchers in the Comparative Genomics Group of the Life Sciences Department and other research groups at the BSC and IRB. The work is in the framework of the research lines of the group, involving in the study of the origin of eukaryotes, their genomes, and their evolution, including the development of new tools and approaches.
The Researcher will work in a highly sophisticated HPC environment, will have access to state-of-the-art systems and computational infrastructures, and will establish collaborations with experts in different areas both at international and local levels, in particular. The Researcher’s tasks will involve applying state-of-the-art phylogenetic methods for the reconstruction of evolutionary processes and the discovery of selective processes and constraints that drive the evolution of gene families in the ancestral eukaryotes.
Key Duties
- Development and application of state-of-the-art phylogenomic analysis methods for the study of relevant evolutionary processes.
- Perform a phylogenetic and comparative analysis of large datasets of protein families from diverse organisms.
- Inference of functional properties of proteins, based on their sequence, reconstruction of potential metabolic properties of ancestral organisms.
- Inference of ancestral evolutionary processes, including horizontal gene transfer, directional selection, gene loss and duplication.
- Explore novel applications for the evolutionary analysis of gene families, including the development of novel computational tools and approaches.
- Preparation and presentation of scientific articles.
- Collaborate in the preparation and presentation of scientific projects.
- Establish and maintain collaborations with national and international researchers.
Termini per aplicar: Dimecres, 16 Agost, 2023
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