PhD: Machine Learning to Recognise and Identify Bird Species from Radar Data

University of Hull

To celebrate the University's research successes, the University of Hull is offering a full-time UK/EU PhD Scholarship or International Fees Bursary for candidates applying the following project in Computer Science.

Closing date: - Monday 4th June 2018

Studentships will start on 17th September 2018

For further information, email the Research Cluster lead, Dr Alastair Ward

Project Description

The Humber estuary is rich in resident bird life and represents a significant corridor for migratory species. However, it is also a highly dynamic and industrialised landscape thus presents a mix of risks, challenges and benefits to the birds that use it. Conversely, the presence of resident and migratory birds along the estuary raises issues for industrial development and, potentially, human and livestock health. In partnership with the Animal & Plant Health Agency we share an ambition to create a new, vibrant research community with an explicit focus on bird ecology and behaviour in order to answer pure and applied questions regarding the use of the landscape by birds and interactions with human interests. Central to the work programme are three PhD Scholarships, all of which will be underpinned by the deployment of a bird detection radar and mobile laboratory at sites at which birds can be directly observed and sampled.

Existing systems for interpreting collected radar data for bird detection rely heavily on human interpretation and annotation. Such annotated data can be used to train machine learning software to perform this task. The project will investigate a number of challenges. The radar data gathered are prone to noise and clutter. Filters need to be designed and implemented that remove such noise and discriminate between bird and non-bird moving targets. State-of-the-art deep learning techniques, such as convolutional neural nets and support vector machines, can be used here. Swarm algorithms can then be investigated in an effort to provide species level identification. The use of intelligent interfaces will enable the data, and its interpretations, to be visualised and interrogated. These advances will enable far deeper insight into the radar data, offering greater efficacy and efficiency to the other projects within this cluster and to future bird radar projects. The successful candidate will be a competent numerical scientist with experience of machine learning, excellent skills in programming and at least an interest in bird ecology and behaviour.

Applicants should have at least a 2.1 undergraduate degree in Computer Science/Mathematics, or related discipline, together with relevant research experience. It is anticipated that the successful applicant will have a 1st class undergraduate degree or Masters level qualification.

To apply for these Scholarships please click on the Apply button below.                                

Full-time UK/EU PhD Scholarships will include fees at the ‘home/EU' student rate and maintenance (£14,777 in 2018/19) for three years, depending on satisfactory progress.

Full-time International Fee PhD Studentships will include full fees at the International student rate for three years, dependent on satisfactory progress.

PhD students at the University of Hull follow modules for research and transferable skills development and gain a Masters level Certificate, or Diploma, in Research Training, in addition to their research degree.

Successful applicants will be informed of the award as soon as possible and by 4th July 2018 at the latest.

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Northern England