Theme: Ecology genetics and evolution  

Description: We are seeking a motivated student to join a project that aims to unravel the complex genetic architecture of gravitropism in plants. This project will utilize innovative tensor and hypergraph methodologies to analyse simulated genetic data, providing novel insights into the evolutionary forces shaping plant growth and response to gravity. The student will be instrumental in applying and further developing a modified Wright-Fisher model of evolution, integrating it with advanced data analysis techniques to explore the nuances of plant genetics and adaptation.

Additional Information: 

Roles and Responsibilities:
• Implement and modify the Wright-Fisher model for gravitropism, incorporating aspects such as mutation, selection, and SNP contributions.
• Analyse genetic data using tensor and hypergraph approaches to identify key genetic interactions and evolutionary patterns.
• Collaborate in developing new hypotheses and testing them against simulated data.
• Contribute to the interpretation of results and the preparation of manuscripts for publication.
• Enrolled in or recently graduated from a degree in Genetics, Bioinformatics, Computational Biology, or a related field.
• Strong computational skills, particularly in R or Python, and familiarity with genetic data analysis.
• An understanding of population genetics models, particularly the Wright-Fisher model.
• Ability to work independently and as part of a team, with strong communication skills.
• Enthusiasm for evolutionary biology and plant genetics research.
What We Offer:
• Opportunity to work on a cutting-edge project at the intersection of computational biology and plant genetics.
• Access to advanced computational resources and datasets.
• Close mentorship from experienced researchers in the field.
• Potential for co-authorship on publications and presentation of research at conferences.
Application Process: Please submit your CV, a brief statement of research interests, and any relevant work or project samples to The ideal candidate will start honours in RQ3 2024 or RQ1 2025.

Contact: Professor Daniel Ortiz-Barrientos