PhD Opportunity - Use of video and laser imaging with AI to quantify bycatch in scallop fisheries, Heriot Watt University

Posted: 16 November 2020

Closing: 30 November 2020

Category: Non MASTS

This PhD is focused on using computer vision and AI to automate the task of collecting and processing data on bycatch composition in fisheries at sea using imaging techniques. Fisheries scientists require information on the composition (species and size of organisms) of bycatch to gain a holistic picture of sources of fishing mortality and thereby improve estimates of fish stock status (health). To date, information on bycatch is usually recorded by observers on board vessels, a process that is time consuming, expensive, and achieves minimal coverage in space and time. Automating the data gathering process would create a step change in our ability to collect data. The project will provide data into the fishery improvement project ‘Project UK’.

The objective of the PhD is to develop the necessary techniques to process and analyse images obtained from an HD camera and a 3D laser scanner. The challenge is to use machine learning to train a model to recognize the catch (scallops) and the bycatch (other species) and to differentiate these images from inert material (e.g. rocks). The reason for using the two approaches (HD camera and laser) is to compare results derived from each or combine the two sources of data in a multimodal systems. The lead supervisor has worked previously with Bangor University and Aberystwyth University to make advances on the camera imaging aspect of the project. This is now at a mature stage with new hardware (i.e. a camera with on-board computing capability). The current state of workstream development means that algorithms have been developed such that video images can be sliced into still frame images of valid records ready for species and size determination. The laser aspect of the project is at a concept phase, but the technique is currently applied at Ulster University to scan seabed morphology and habitats, and hence it is known that the application would work in the proposed context.

The multidisciplinary nature of the project requires a large supervisory team. It is expected that the student will be based primarily at Heriot-Watt University but will be expected to spend several months working with teams at Aberystwyth University and Ulster University.

Prof Michel Kaiser (HWU)
Dr Marta Vallejo (HWU)
Dr Chris McGonigle (Ulster)
Dr Bernie Tiddeman (Aberystwyth)
Dr Marie Neal (Aberystwyth)
Dr Natalie Hold (Bangor)

Candidates that have some appreciation of fisheries or practical experience of working at sea would be preferred. The PhD will require sea-time on board fishing vessels to test and validate the results collected by the systems developed as part of the PhD. As a result, you must be capable of passing an ENG1 medical and survival at sea course. You will embrace new challenges and environments and be able to fit into new teams rapidly. You must be able to describe complex issues in a means that is accessible to fishermen with whom you will work.

HOW TO APPLY
You are requested to send a cover letter stating why you are interested in the PhD, what ideas you could bring to the project, and outline any relevant experience. You are also requested to submit a CV with all qualifications to date. The cover letter and CV should be sent to Prof Michel Kaiser ().

In addition, you must complete our online application form and select PhD Marine Biology and include the full project title, reference number and supervisor on your application form. Ensure that all fields marked ‘required’ are complete. You must complete the section marked project proposal; upload a supporting statement documenting your reasons for applying to this particular PhD project, and why you are an ideal candidate for the position. You will also need to provide a CV, a copy of your degree certificate/s and relevant transcripts. You will be asked to enter details of an academic referee who will be able to provide a technical reference. Until your nominated referee has uploaded their statement, your application will not be marked as complete and will not be considered by the review panel. You must also provide proof of your ability in the English language (if English is not your mother tongue or if you have not already studied for a degree that was taught in English within the last 2 years). We require an IELTS certificate showing an overall score of at least 6.5 with no component scoring less than 6.0 or a TOEFL certificate with a minimum score of 90 points.
Funding Notes
This project is available to home (UK) or EU students. The project is funded for 3.5 years and covers the PhD fees and stipend (currently £15,285 per annum) and has a generous travel and equipment budget.

The successful candidate will have a BSc (2:1 or higher) and MSc (distinction) or equivalent, and ideally experience in computer science, modelling, image analysis or engineering with some experience of applying these skills to other disciplines. You will have good programming skills, preferably in Python or other advanced programming languages. Knowledge of Tensorflow, Keras, Pytorch and/or other deep learning frameworks would be advantageous.