PhD Studentship: Probabilistic Combinatorics
Listed on 2026-10-21
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Research/Development
Research Scientist, Data Scientist, Research Analyst
The probabilistic method is a powerful tool which has been especially influential in the fields of combinatorics and computer science. In the context of combinatorics, this method was pioneered by Erdős, who demonstrated that random constructions could often be effective in settings where explicit constructions are infeasible. These ideas, establishing a correspondence between counting and probability, allow for the application of tools from probability theory to combinatorial problems and motivate the study of the typical properties of various combinatorial models, such as the Erdős–Rényi random graph, and discrete random processes.
The aim of this project is for the student to develop an understanding of these tools and to apply these techniques to open research problems in the field.
The project will be supervised Dr by Joshua Erde ().
Entry requirements:We are looking for an enthusiastic and highly-motivated graduate with
- A first class degree in Mathematics at the Master’s level (or equivalent);
- A strong background in combinatorics and discrete probability, or related fields;
- Good communication skills (oral and written).
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