About the Project

Faculty of Health and Life Sciences 

Department of Biological and Medical Sciences

3 Year, full-time PhD studentship

Eligibility: Home UK/EU and International applicants

Bursary per annum: Bursary equivalent to UKRI national minimum stipend plus fees (current 2022/23 bursary rate is £17,668)

University fees and bench fees: University fees and bench fees will be met by the University for the 3 years of the funded Studentship. Visa and associated costs are not funded. International applicants can visit https://www.brookes.ac.uk/students/isat/ for further information

Closing date:  23 February 2023 

Interviews: Provisionally 13,14 March 2023

Start date:  September 2023

Project Title: Investigating the Contribution of Morphological Divergence to Behaviour using AI

Director of Studies: Daniela Santos-Nunes 

Other Supervisors: Fabio Cuzzolin

Requirements:

Applicants should have a first or upper second-class honours degree from a Higher Education Institution in the UK or acceptable equivalent qualification. EU Applicants must have a valid IELTS Academic test certificate (or equivalent) with an overall minimum score of 7.0 and no score below 6.0 issued in the last 2 years by an approved test centre.  

Project Description: 

Identifying the genes underlying phenotypic divergence is crucial to understanding how new phenotypes arise and species differentiate. Recently, we identified some of the genes that contribute to divergence in size and shape of male genitalia between two species of fruit flies (Hagen et al., 2019, 2021). Genital structures evolve very quickly between closely related species (Eberhard, 2010) and are known to affect mating behaviour and reproductive fitness (Frazee and Masly, 2015, LeVasseur-Viens et al., 2015). However, identifying behavioural differences encoded by the effect of these genes on male genital morphology necessitates large-scale experiments under tightly controlled conditions.  Recent advances in automated tracking and behaviour annotation make high throughput analysis of behaviour now possible. 

This project aims to implement a high-throughput pipeline for mating behaviour analysis, using machine-learning techniques such as deep neural networks, to analyse video data acquired from custom-made behaviour arenas. Objective 1: To use males that differ in the species-specific allele they carry for each of the focal genes to determine if their effect on genital morphology results in differences in stereotypical mating, including the nature and timing of those differences. Objective 2: To automate the discovery of new behavioural phenotypes and apply the pipeline in more complex contexts (e.g. multiple mating pairs),  leading to better understanding of group mating behaviour in the wild. Results will provide fundamental insight into the proximate causes of behavioural evolution driving speciation. 

There is an additional requirement to undertake up to 6 hours undergraduate teaching/week during semesters and to participate in a teaching skills course without further remuneration.

Contact: msantos-nunes@brookes.ac.uk

How to apply: Applicants should visit the project webpage for instructions on how to submit an online application