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Postdoctoral Researcher Precisiontox, Barcelona
Client: Center for Genomic Regulation
Location: Barcelona, Spain
Job Category: Other
EU work permit required: Yes
Job Reference: 705218934772596736032460
Job Views: 1
Posted: 31.03.2025
Expiry Date: 15.05.2025
Job Description:
The Institute
The Centre for Genomic Regulation (CRG) is an international biomedical research institute of excellence, based in Barcelona, Spain, with more than 400 scientists from 44 countries. The CRG is composed of an interdisciplinary, motivated, and creative scientific team supported by a flexible and efficient administration and high-end innovative technologies.
In April 2021, the Centre for Genomic Regulation (CRG) received the renewal of the 'HR Excellence in Research' Award from the European Commission. This is a recognition of the Institute's commitment to developing an HR Strategy for Researchers, designed to align practices and procedures with the principles of the European Charter for Researchers and the Code of Conduct for the Recruitment of Researchers.
Please check out our Recruitment Policy.
The role
The overarching theme of the research in our lab is understanding the information encoded in genomic sequences and how this information is processed in the pathway leading from DNA to protein sequences. We are particularly interested in the epigenetic regulation of gene expression and RNA processing, the relationship between molecular phenotypes and higher-order endophenotypes and organismal phenotypes, and the identification of functional regions on the genome of all living beings. Our group is primarily computational, engaging in large-scale data analysis and method development, with an important experimental component as well.
PrecisionTox is a European funded project aimed at establishing a new, 3Rs-compliant (Replacement, Reduction, Refinement), cost-effective testing paradigm for chemical safety assessment—Precision Toxicology—revolutionizing regulatory toxicology, replacing animal testing, reducing uncertainty, and determining safety factors in assessing risks to human health. This goal will be accomplished by identifying molecular key event biomarkers predictive of chemically induced adverse health effects in humans, feeding directly into regulatory and industry practice through the systematic use of distantly related animal species and a highly interdisciplinary mix of genomics, metabolomics, evolutionary theory, quantitative genetics, data science, toxicology, and law.
Within this project, our group at the CRG focuses on the analysis of bulk and single-cell RNA-seq from five different model species (Danio, Xenopus, Caenorhabditis, Daphnia, and Drosophila) after treatment with selected putative cardio, neuro, and hepatotoxic compounds. Our aim is to employ existing and developing novel approaches—including Machine Learning Methods—to predict the impact of chemical compounds on humans based on their effects on the transcriptomes of the model species, particularly in predicting impacts on co-expression networks.
About the lab
The overarching theme of the research in our lab is understanding the information encoded in genomic sequences and how this information is processed in the pathway leading from DNA to protein sequences. We are particularly interested in the epigenetic regulation of gene expression and RNA processing, the relationship between molecular phenotypes and higher-order endophenotypes and organismal phenotypes, and the identification of functional regions on the genome of all living beings. Our group is primarily computational, engaging in large-scale data analysis and method development, with an important experimental component as well.
Whom would we like to hire?
Professional experience
Must Have:
* You have a strong computational background.
* You have experience in the development and/or implementation of algorithms and/or computational pipelines.
Desirable but not required:
* You have background/experience in building Statistical and/or Machine Learning methods.
* You have previous experience in building and interacting with relational databases (e.g., PostgreSQL) and APIs.
* You have experience in the analysis of large-scale omics data, specifically (single-cell/bulk) RNA-seq, including QTL analysis and quality control.
Education and training
You hold a PhD in Bioinformatics, Biology, Machine Learning, Statistics, Physics, Mathematics, Chemistry, or related areas.
Languages
You have a high level of spoken and written English.
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