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Postdoctoral Researcher PrecisionTox

Postdoctoral Researcher PrecisionTox

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 by an interdisciplinary, motivated and creative scientific team which is supported both by a flexible and efficient administration and by high-end and 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 bring the practices and procedures in line with the principles of the European Charter for Researchers and the Code of Conduct for the Recruitment of Researchers (Charter and Code).

Please, check out our Recruitment Policy

The role

The overarching theme of the research in our lab is the understanding of the information encoded in genomic sequences, and how this information is processed in the pathway leading from DNA to protein sequences. More specifically, we are 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 mostly computational, and we do both large-scale data analysis and development of methods, but it has also an important experimental component. We participate in many large scale international functional genomics projects, such as ENCODE, GTEx, BluePrint and others.

PrecisionTox is an European funded project, the overarching aim of which is to establish a new, 3Rs- compliant (Replacement, Reduction, Refinement), cost-effective testing paradigm for chemical safety assessment — Precision Toxicology — that revolutionizes regulatory toxicology, replaces animal testing, reduces uncertainty, and determines safety factors in assessing risks to human health. This goal will be accomplished by identifying molecular key event (KE) biomarkers, predictive of chemically induced adverse health effects in humans, that feed directly into regulatory and industry practice via the systematic use of distantly related animal species from across the tree of life and the 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 emerging from other efforts within PhyloTox. Our aim is to employ existing and developing novel approaches--including Machine Learning Methods, to predict the impact in human of the chemical compounds, based on the impact that they have in the transcriptomes of the model species (in particular by predicting the impact on co-expression networks).  This project fits overall within a larger overarching goal in our group of developing methods to relate genome to phenome across the tree of life.

About the lab

The overarching theme of the research in our lab is the understanding of the information encoded in genomic sequences, and how this information is processed in the pathway leading from DNA to protein sequences. More specifically, we are 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 mostly computational, and we do both large-scale data analysis and development of methods, but it has also an important experimental component. We participate in many large scale international functional genomics projects, such as ENCODE, GTEx, BluePrint and others.

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 of computational pipelines

Desirable but not required/ Nice to have

• You have background/experience in building Statistical and/or Machine Learning (e.g. explainable/supervised/unsupervised data integration) 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) RNAseq. Experience with QTL analysis and quality control

Education and training

• You hold a PhD in Bioinformatics or in Biology, Machine Learning, Statistics,  Physics, Mathematics, Chemistry or related areas

Languages

• You have a high level of spoken and written English.

Technical skills

• You have strong programming skills, for example Python, C, C++, MATLAB,  R, etc.
• You have knowledge of data visualisation methods (e.g. PCA, UMAP, t-SNE, etc)
• You have knowledge at bash scripting in a Linux environment, ideally tailored to an HPC infrastructure
• You have knowledge of multivariate statistics, Deep Learning Libraries: TensorFlow, Pytorch
• You know how to containerized workflows and DSLs: Nextflow, SnakeMake,
• You know how to use collaborative tools

Competences

• You have highly developed organisational skills
• You have the capacity to work independently, but also the ability to interact with others, both with colleagues within the group and from the project consortium.
• You have good (academic) writing and presentation skills
• You have imagination, motivation and curiosity
• You are proactive, independent and have critical thinking

The Offer – Working Conditions

  • Contract duration:  Long-term position subject to project duration
  • Estimated annual gross salary: A competitive salary will be provided, which will be well matched relative to the cost of living in Barcelona, and adjusted according to experience.
  • Target start date: As soon as possible

We provide a highly stimulating environment with state-of-the-art infrastructures, and unique professional career development opportunities. To check out our training and development portfolio, please visit our website in the training section.

We offer and promote a diverse and inclusive environment and welcomes applicants regardless of age, disability, gender, nationality, ethnicity, religion, sexual orientation or gender identity.

The CRG is committed to reconcile a work and family life of its employees and are offering extended vacation period and the possibility to benefit from flexible working hours.

Application Procedure

All applications must include:
1. A motivation letter addressed to Dr Roderic Guigó.
2. A complete CV including contact details.
3. Contact details of two referees.

All applications must be addressed to Dr. Roderic Guigó and be submitted online on the "Apply" button below.

Selection Process

₋ Pre-selection: The pre-selection process will be based on qualifications and expertise reflected on the candidates CVs. It will be merit-based.
₋ Interview: Preselected candidates will be interviewed by the Hiring Manager of the position and a selection panel if required.
₋ Offer Letter: Once the successful candidate is identified the Human Resources department will send a Job Offer, specifying the start day, salary, working conditions, among other important details.

Deadline: Please submit your application by May 15th 2022

Suggestions: The CRG believes in ongoing improvement and promotes a culture of feedback. This is one of the reasons we have in place, at your disposal as a candidate, a mechanism to gather your suggestions/complaints concerning your candidate experience in our recruitment processes. Your feedback really matters to us in our aim at creating a positive candidate journey. You can make a difference and help us improve by letting us know your suggestions through the following form.

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