Sandra Beleza
1 year ago
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Biological Sciences University of Leicester in United Kingdom
Degree Level
PhD
Field of study
Population Genetics
Funding
These PhD studentships are fully funded, covering tuition fees and providing a stipend. Specific stipend amount is not mentioned. Funding is for the duration of the PhD and includes training in bioinformatics, statistics, and laboratory methods.
Deadline
Expired
Country
United Kingdom
University
University of Leicester

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About this position
The University of Leicester is offering two fully funded PhD studentships focused on the evolutionary mechanisms in bacteria that lead to antibiotic resistance and pathogenicity. Project 1 investigates the epidemiology, genetic basis, and molecular evolution of antimicrobial drug resistance in Helicobacter pylori using population models and advanced computational analyses. Project 2 explores the evolutionary mechanisms that drive pathogens from commensality to virulence, integrating large-scale genomic datasets with simulation modelling and evolutionary inference. Both projects are supervised by Dr Sandra Beleza and Dr Fabian Freund, whose research groups are internationally recognised for their work in population genetics, microbiology, and bioinformatics.
Students will join an interdisciplinary team and receive comprehensive training in bioinformatics, statistics, and laboratory methods. Applicants should have a strong academic record in Biological Sciences, with relevant experience in microbiology, genetics, or bioinformatics.
The studentships are fully funded, covering tuition and providing a stipend. For more information and to apply, visit the project links or contact the supervisors. The application deadline is not specified; interested candidates should apply as soon as possible.
Funding details
These PhD studentships are fully funded, covering tuition fees and providing a stipend. Specific stipend amount is not mentioned. Funding is for the duration of the PhD and includes training in bioinformatics, statistics, and laboratory methods.
What's required
Applicants should have a distinction or high 2:1 in a relevant Master's or Bachelor's degree in Biological Sciences, including Microbiology, Genetics, and/or Bioinformatics. A strong academic record is required. Experience in computational analysis, population genetics, or mathematical modelling is desirable. No specific language test or GPA mentioned.
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