Genetic mechanisms of metabolic rate control in birds and mammals
Not stated
- Location
- London, United Kingdom
- Funding
- Funded PhD Project (Students Worldwide)
- Application deadline
- 2 November 2026
About the project
About the Project A 2027 Crick PhD project with Katya Osipova. Project background and description Metabolic rate, the speed at which organisms extract energy from nutrients, is a fundamental and universal property of life. It defines the efficiency of energy turnover and plays a crucial role in determining cell fate. However, the genetic elements controlling metabolic rate remain largely unknown. This gap in our knowledge presents a barrier to understanding and manipulating cellular metabolism for various applications, from basic research to therapeutic interventions. Metabolic rates vary tremendously across animals, making the animal kingdom an ideal system for studying the genetic basis of metabolic rate control. In this project, we will leverage natural variation in metabolic rates across mammals and birds to identify key genetic elements driving these differences. In our group, we use comparative genomics combined with experimental validation to uncover the genetic basis of phenotypes [1-4]. We will apply state-of-the-art evolutionary rate-based methods as well as newly developed machine-learning-based approaches to link changes in DNA to shifts in phenotype evolution. This project aims to build the first large-scale, comparative genomic map of genes and regulatory elements involved in metabolic rate control across true endotherms. Candidate background This project is aimed at highly motivated candidates with a strong interest in evolution and genomics, and a willingness to engage with large-scale genomic and transcriptomic data analysis. Prior experience in computational biology, evolution, or genomics is a plus, though not required, as training will be provided. There will be a lot of flexibility in the direction of the project development. Depending on the candidate's interests and strengths, the work can remain primarily computational or extend into lab-based validation of key candidates. Lab-specific question Looking at the research undertaken in our lab, what aspect would you be most interested in exploring further? Drawing on your own research experience, what perspective, skill or approach would you bring to investigating it?