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School of Biological and Behavioural Sciences

Decoding and mapping Earth's species interactions with artificial intelligence

Project Overview

Would you like to take your career in ecology, artificial intelligence (AI) or conservation biology to the next level in one of the world's most exciting cities? The McFadden Lab at Queen Mary University of London is offering a fully-funded 4-year PhD studentship with flexibility to decide on the research topic. Current research in the lab is broadly focused on interactions between plants and animals such as seed dispersal and pollination, and how emerging AI and global mapping tools can be used to study and conserve these interactions from local to global scales. Based on your interests, the PhD project will focus on one or both of the below research questions:

  1. Can we teach AI systems to understand ecological interactions using computer vision or multi-modal approaches, and how can we use the models to learn about the biology of plant-animal interactions?

  2. What are the major global patterns of species interaction diversity, how have these patterns been formed and what are the main threats to this understudied dimension of diversity?

In your application, please indicate which of the two above research questions you are most interested in, or whether you are interested in working on both questions.

Research Environment

The project will take place within the interdisciplinary, dynamic and welcoming research environment of the McFadden Lab (https://mcfaddenecology.com) at Queen Mary University of London, with the opportunity for collaborations with world-class institutions in London such as Kew Gardens, the Natural History Museum, the London Zoo and the Alan Turing Institute. Campus resources include the large computing cluster Apocrita and the Digital Environment Research Institute. The PhD student will receive training in R coding, data synthesis and analysis, computer vision and global mapping depending on student interests.

Find out more about the School of Biological and Behavioural Sciences on our website.

Keywords: Species interactions, neural networks, seed dispersal, functional traits, biogeography, global ecology

Entry Requirements

We are looking for candidates to have or expecting to receive a first or upper-second class honours degree and a Master’s degree in an area relevant to the project such as biology, ecology or data science.  

Knowledge of ecology, species interactions, data science, the R programming language, global mapping, computer vision and / or machine learning would be highly advantageous but are not required.

You must meet the IELTS requirements for your course and upload evidence before CSC’s application deadline, ideally by 1st March 2025. You are therefore strongly advised to sit an approved English Language test as soon as possible, where your IELTS test must still be valid when you enrol for the programme.

Please find further details on our English Language requirements page.

How to Apply

Formal applications must be submitted through our online form by 29th January 2025 for consideration. Please identify yourself as a ‘CSC Scholar’ in the funding section of the application.

Applicants are required to submit the following documents:

  • Your CV
  • Personal Statement
  • Evidence of English Language e.g.) IELTS Certificate
  • Copies of academic transcripts and degree certificates
  • References

Find out more about our application process on our SBBS website.

Informal enquiries about the project can be sent to Dr Ian McFadden AT i.mcfadden@qmul.ac.uk Admissions-related queries can be sent to sbbs-pgadmissions@qmul.ac.uk

Shortlisted applicants will be invited for a formal interview by the supervisor. If you are successful in your QMUL application, then you will be issued an QMUL Offer Letter, conditional on securing a CSC scholarship along with academic conditions still required to meet our entry requirements.

Once applicants have obtained their QMUL Offer Letter, they should then apply to CSC for the scholarship with the support of the supervisor.

For further information, please go to the QMUL China Scholarship Council webpage.

Apply Online

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