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Postdoctoral Researcher in the group 'Evolutionary Processes Modeling’

Postdoctoral Researcher in the group 'Evolutionary Processes Modeling’

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

We are looking for a postdoctoral researcher to join the “Evolutionary Processes Modeling” group. We use computational analysis of sequencing data together with population genetics predictions and statistical modeling to answer questions about mutational processes and selective pressures in cancer cells and the human population. The ideal candidate should be highly motivated and eager to work on evolutionary and biological problems through the use and development of computational and statistical approaches.

About the group

Cancer is a genetic disease, subject to population genetics forces like mutation, selection and stochasticity. Our group is particularly interested in how the evolution and survival of cancer cell populations relies on mutation influx as well as in selection inference from observed mutation data. To this end, we develop mathematical and computational approaches to estimate mutation rates and selection. Estimates of the strength of selection in cancer allow for a prioritization of genes and non-coding regions by their disease relevance, with the ultimate goal of promoting therapeutic advances. Coding sequences of cancer tumors not only exhibit positively selected mutations that drive cancer (www.nature.com/articles/s41588-019-0572-y), but there also exists a small fraction of genes that the tumor cannot afford to lose (www.nature.com/articles/ng.3987). In addition to genes, cancer driver loci can occur in the non-coding part of the genome (www.nature.com/articles/s41467-017-00100-x).

We are also interested in mutation rates and selection inference in the context of human genetic variation, including polymorphisms (http://www.nature.com/articles/ng.3831; academic.oup.com/mbe/article-abstract/36/8/1701/5475505) and de novo variants (www.nature.com/articles/s41467-020-17162-z). Here, a particular focus of the group lies on the description of purifying selection in humans and across species, accounting for mutational processes as well as the effects of genetic drift.

The Evolutionary Processes Modeling lab was established in October 2018 and is part of the “Bioinformatics and Genomics” program at the CRG. Further information can be found at https://weghornlab.net/ and at www.crg.eu/en/programmes-groups/weghorn-lab.

Whom would we like to hire?

Professional experience

• You have worked with DNA sequencing or other biological datasets
• You are familiar with the principles of population genetics

Education and training

• You hold a PhD degree in population genetics, physics, statistics, bioinformatics, or a related discipline

Languages

• You are fluent in English

Technical skills

• You have experience with computational data analysis
• You are familiar with modeling and statistical analysis

Competences

• You have highly developed organization skills
• You have good communication skills
• You have the capability to as part of a team and/or independently

The Offer – Working Conditions

Contract duration: 1 year with possibility of extension.
Estimated annual gross salary: Salary is commensurate with qualifications and consistent with our pay scales.
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. Donate Weghorn.
2. A complete CV including contact details and a list of publications.
3. Contact details of two referees.

All applications must be submitted online through the "Apply" button below.  

Selection Process

Pre-selection: The pre-selection process will be based on qualifications and expertise reflected in the candidates' CVs. It will be merit-based.

Interview: Pre-selected 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 November 30th, 2021.

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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