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PhD Studentship: Modelling Animal Viewscapes Using LiDAR and Species-Specific Visual Fields

Manchester Metropolitan University

Qualification Type: PhD
Location: Manchester
Funding for: UK Students
Funding amount: See advert
Hours: Full Time
Placed On: 24th February 2026
Closes: 27th March 2026
Reference: SciEng-CB-2026-27-Modelling Animal Viewscapes
 

Applications are welcomed for a fully-funded PhD studentship with Manchester Metropolitan University and Chester Zoo. Our team combines expertise in sensory ecology, evolutionary biology, and 3D imaging, to develop new approaches for understanding how animals perceive and respond to complex environments.

Modern zoos must balance animal welfare and natural behaviour with husbandry practice, visitor experience, and education. Doing so requires an understanding of enclosures as animals perceive them. While the idea of zoo soundscapes is growing, ‘viewscapes’ (what animals can see, how visible they are to visitors/conspecifics, and where visual refuges occur) remain understudied. Their relevance extends beyond zoos, as visibility and access to visual refuge also structure interactions in-situ. This PhD will build a toolkit to quantify viewscapes, integrating species-specific visual fields to map visibility across space and guide enclosure design.

You will join a vibrant research community and receive supervision from an experienced team spanning Manchester Met and Chester Zoo. You will benefit from a skills training programme through our Doctoral College, and will be based in the Faculty of Science and Engineering, and enrolled as a Chester Zoo Conservation Scholar.  

Project aims and objectives

This project will develop a computational pipeline to quantify viewscapes for both animals and humans. This will include the specific objectives:

  • Develop species-neutral viewscapes using terrestrial LiDAR-derived 3D enclosure models and ray-tracing modelling.
  • Identify species-specific visual field characteristics, and investigate the benefits of incorporating these into viewscape modelling.
  • Develop and test aspects of enclosure design in order to make future recommendations.

Funding

Both Home and International students can apply. Home tuition fees will be covered for the duration of the three-year award, which is £5,238 for the year 2026/27. Eligible international students will need to make up the difference in tuition fee funding (Band 3 for the year 2026/27).

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £21,805 for the academic year 2026/27.

Specific requirements of the candidate

Essential:

  • A first class or 2.1 degree (or equivalent) in Biology, Zoology, Computer Science, Architecture, or a related field
  • Strong coding skills (Python preferred)
  • Experience with processing and analysing 3D data
  • Excellent written communication skills
  • An interest in interdisciplinary research and enthusiasm for developing novel methods for improving animal husbandry, welfare and conservation

How to apply

Dr Charlotte Brassey (c.brassey@mmu.ac.uk) will lead the project as your Principal Supervisor. You are encouraged to apply for this opportunity directly by following the steps outlined below, without an informal discussion. If you have any queries in relation to this project, please get in touch with the proposed Principal Supervisor.

To apply you will need to complete the online application form for a full-time or part-time PhD in Biological Science.

Please complete the Doctoral Project Applicant Form, and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest. 

Please upload these documents in the supporting documents section of the University’s Admissions Portal.

Applications closing date: 27 March 2026

Expected start date: October 2026.

Please quote the reference: SciEng-CB-2026-27-Modelling Animal Viewscapes

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