PhD student: Computational models of genotype-phenotype maps and evolution

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 an enthusiastic and motivated PhD student who will work on models of variation in evolving populations. They will develop and carry out computer simulations and supplement these with analytic calculations. They will collaborate in the preparation of scientific papers and present their results at scientific seminars and conferences.

About the research team

The successful candidate will work at the Barcelona Collaboratorium for Modelling and Predictive Biology, a new space for computational and theoretical biology launched as a joint initiative of two leading life science institutes - the CRG and EMBL Barcelona. Each area of biology has its own unique features, but concepts and tools from one discipline can provide important fresh insights and new perspectives into another. The Collaboratorium’s focus is to bring together experts from different disciplines, into the same space, from molecular, cellular and tissue biology, up to epidemiology and ecosystems. Thus, the PhD student will be part of a lively interdisciplinary community of researchers applying quantitative concepts to biological phenomena.

Within the Barcelona Collaboratorium, the PhD project will be supervised by Dr Nora Martin. Her work uses modelling and theory to elucidate a key component of quantitative models of evolution: molecular and phenotypic changes introduced by variation through random mutations. This is addressed using the general framework of a genotype-phenotype (GP) map. GP maps describe how genotypic changes are translated to higher-order phenotypic characteristics. One central model in the field focuses on mutational changes in folded RNA secondary structures. Results from established models like RNA have a broad relevance because they can often be applied to other examples, ranging from other macromolecules to beyond the molecular scale. By improving such GP map models, the aim is to increase their biological realism and thus make progress towards models that can be compared directly to the rapidly increasing amount of available biological data.

Further information can be found on Nora Martin’s Google Scholar page or in a recent perspectives paper.

Whom would we like to hire?

Education and training

• The candidate must hold (by the start date) a Master's degree (300 ECTS credits), preferably in a highly quantitative discipline (Physics/Mathematics/Computational Biology or a related field). The candidate must have a proven track record in quantitative work and a strong interest in getting immersed in a biological research area.

Languages

• The candidate must be proficient in English (spoken and written).

Technical skills

• Programming skills, ideally in Python. Experience with computer clusters (shell scripting) are a plus, but not required.
• Experience in computational modelling, ideally a “bottom-up” approach of building models and running simulations, rather than a “top-down” approach of using code for data analysis.
• Proven analytic and quantitative skills, and the ability and motivation to acquire new knowledge (both biological and mathematical/computational).

Competences

• Organised, structured, self-motivated and conscientious working style.
• Ability to communicate results in a clear and structured way, in presentations and in writing.
• Excellent interpersonal and communication skills, and the ability to function as part of a team.
• Motivation to work in an interdisciplinary environment.

The Offer – Working Conditions

• • Contract duration: 4 years
  • Estimated annual gross salary: Salary is commensurate with qualifications and consistent with our pay scales
  • Target start date: ideally late 2023/early 2024

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 Nora Martin.
2. A complete CV including contact details.
3. University transcripts (Bachelor & master's degree)
4. Contact details of two referees

All applications must be addressed to Dr Nora Martin and be submitted online on the CRG Career site - http://www.crg.eu/en/content/careers/job-opportunities

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 the CRG Graduate Committee.

• Offer Letter: Once the successful candidate is identified the People department will send a Job Offer, specifying the start day, salary, working conditions, among other important details.

Deadline: Please submit your application by November 11^th, 2023.