Job Reference
47_26_LS_CG_R1
Position
PhD student - Phylogenomics (R1)
Closing Date
Sunday, 15 February, 2026
Reference:
47_26_LS_CG_R1
Job title:
PhD student - Phylogenomics (R1)
About BSC
The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for EuroHPC JU, the Joint Undertaking that leads large-scale investments and HPC provision in Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 1000 staff from 60 countries.
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We are particularly interested for this role in the strengths and lived experiences of women and underrepresented groups to help us avoid perpetuating biases and oversights in science and IT research. In instances of equal merit, the incorporation of the under-represented sex will be favoured.
We promote Equity, Diversity and Inclusion, fostering an environment where each and every one of us is appreciated for who we are, regardless of our differences.
If you consider that you do not meet all the requirements, we encourage you to continue applying for the job offer. We value diversity of experiences and skills, and you could bring unique perspectives to our team.
Context And Mission
The Computational Genomics group, led by ICREA professor Toni Gabaldón, is looking for a PhD candidate to work in the context of phylogenomics.
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 ), which is jointly affiliated to 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 an Moore-Simons fundations 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 In this context we are looking for a motivated postdoc with expertise in phylogenetics and evolutionary biology to work in a phylogenomic projects aimed at faithfully reconstructing the evolutionary history of thousands of gene families, to discover ancient trends in gene family evolution. The candidate will work in collaboration with other researchers in the Comparative Genomics Group of the Life Sciences Department as well as 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
1. Development and application of state-of-the-art phylogenomic analysis methods for the study of relevant evolutionary processes.
2. Perform phylogenetic and comparative analysis of large datasets of protein families from diverse organisms.
3. Inference of functional properties of proteins, based on their sequence, reconstruction of potential metabolic properties of ancestral organisms.
4. Inference of ancestral evolutionary processes, including horizontal gene