Vacancies

A full and update list of vacancies

Academic postions

Lecturer / Senior Lecturer / Reader in Applied Mathematics

Applications for the post are welcome in any research areas in Applied Mathematics (broadly construed and including integrable systems and mathematical physics), that complement and/or make links between the existing strengths within the School. The post-holder will develop, lead and sustain research of international standard in Applied Mathematics; contribute to teaching, assessment, project supervision and curriculum design at undergraduate and postgraduate levels; and participate in School management and organisation.

For further information and details on how to apply please visit:

Lecturer/Senior Lecturer/Reader in Applied Mathematics 

Closing Date - 19th May 2024

Postdoctoral postions

Current opportunites can be found here

Professional, Administrative and Support opportunities

No current opportunities

Funded Ph.D opportunities

Statistical methodology for Assessing the impacts of offshore renewable developments on marine wildlife (PhD)

Supervisors: Janine Illian
Relevant research groups: Modelling in Space and Time, Bayesian Modelling and Inference, Computational Statistics, Environmental, Ecological Sciences and Sustainability

(jointly supervised by Esther Jones and Adam Butler, BIOSS)

Assessing the impacts of offshore renewable developments on marine wildlife is a critical component of the consenting process. A NERC-funded project, ECOWINGS, will provide a step-change in analysing predator-prey dynamics in the marine environment, collecting data across trophic levels against a backdrop of developing wind farms and climate change. Aerial survey and GPS data from multiple species of seabirds will be collected contemporaneously alongside prey data available over the whole water column from an automated surface vehicle and underwater drone.

These methods of data collection will generate 3D space and time profiles of predators and prey, creating a rich source of information and enormous potential for modelling and interrogation. The data present a unique opportunity for experimental design across a dynamic and changing marine ecosystem, which is heavily influenced by local and global anthropogenic activities. However, these data have complex intrinsic spatio-temporal properties, which are challenging to analyse. Significant statistical methods development could be achieved using this system as a case study, contributing to the scientific knowledge base not only in offshore renewables but more generally in the many circumstances where patchy ecological spatio-temporal data are available. 

This PhD project will develop spatio-temporal modelling methodology that will allow user to anaylse these exciting - and complex - data sets and help inform our knowledge on the impact of off-shore renewable on wildlife.