[visionlist] Available PhD Position at the intersection between AI and Marine Conservation

[Amir Aly]

Dear All,

We have an available PhD position (*Monitoring health and unlocking social
behaviour in bottlenose dolphins with interdisciplinary next-generation
technology*) at the intersection of Marine Conservation and AI. More
details are available here: Link
<https://www.plymouth.ac.uk/schools/school-of-biological-and-marine-sciences/monitoring-health-and-unlocking-social-behaviour-in-bottlenose-dolphins-with-interdisciplinary-next-generation-technology>
. The closing date for applications is *22/04/2024**.*

Project description
Monitoring health and social behaviour in cetacean populations is required
for population management and quantification of human impacts. Measures of
individual fitness, survival, reproductive success, and sociality can have
far-reaching implications for wildlife management and conservation, as
populations adapt, or not, to human disturbance. Quantifying individual
interactions is the foundation of social behaviour and cetaceans arguably
demonstrate some of the most complex social systems in the mammalian world.
However, the nature of social relationships in cetaceans remains poorly
studied. Cetaceans provide unique research challenges that can constrain
data collection and prevent multimodal inference. Recent developments in
marine robotics, artificial intelligence (AI) and bioacoustics open
opportunities for a technology-driven approach for conservation and
behavioural research. AI-based techniques employing machine learning to
analyse unoccupied aerial systems (UAS)-captured footage, and acoustic data
need integration into tools to extract behavioural patterns and allow
application to conservation research. The Scottish bottlenose dolphin
project is one of the longest running individual-based studies of dolphins
in the world, with multi decade sighting histories and life history data.
This population has high societal importance, with core habitat impacted by
coastal developments and in key areas for UK renewable energy. This project
is an opportunity to integrate new generation technologies and contribute
vital population and individual level information for conservation
management and compliance monitoring for UK renewables.


*Project aims and methods*

This PhD project will integrate technology-driven data collection across
bioacoustics, marine robotics and artificial intelligence to advance animal
behaviour research. The project has four main research objectives:

   - Synchronise and integrate data collection of vocal signals and
   movement patterns of wild dolphin groups.
   - Determine social relationships, group behaviour and population
   demographics from boat-based and UAS still and video imagery.
   - Explore the boundaries of social behaviour using AI for tracking
   individuals.
   - Integrate and disseminate data across research and industrial sectors
   for policy and conservation management of this protected population.

*Research Methodology*
The student will collect acoustic, behavioural and UAS data during the
annual summer field campaigns run by the Lighthouse Field Station based in
Cromarty, Scotland. They will use a modified multi-rotor UAS, fitted with a
laser altimeter to collect high-resolution still and video imagery of
dolphin groups to verify individual identity information from known
bottlenose dolphins within the population, and deploy hydrophones to record
underwater acoustics. The student will explore dolphins’ fine-scale spatial
interactions and individual movement trajectories and their link to
acoustics, as well as morphometric and demographic data. The student will
utilize and integrate a suite of AI methodologies to test hypotheses
relating to the influence of social relationships and individual identity
on group movement and acoustics in dolphins.

Training
This project will provide the student with multi-disciplinary skills
development and training across bioacoustics, behavioural ecology and
artificial intelligence. They will complete small boat work and field data
collection at a world leading field station enhancing their data collection
skills and providing benefits of interaction across two institutions. The
student will also benefit from access to the Scottish bottlenose dolphin
project longitudinal dataset to inform the individual level analysis that
underpins this project, as well as a highly skilled field team to
facilitate data collection and individual training. They will receive
dedicated training in UAS operation and maintenance and depending on
background may receive training in ecology, bioacoustics, artificial
intelligence applications and R and Matlab programming.

*Supervisory team*

The project will be supervised by Dr. Nicola Quick
<https://www.plymouth.ac.uk/staff/nicola-quick>, Dr. Clare Embling
<https://www.plymouth.ac.uk/staff/clare-embling>, Dr. Barbara Cheney
<https://www.abdn.ac.uk/sbs/people/profiles/b.cheney>, and Dr. Amir Aly
<https://www.plymouth.ac.uk/staff/amir-aly>

If you have questions, pls don't hesitate to ask,

Regards
----------------

*Dr. Amir Aly*

Lecturer in Artificial Intelligence and Robotics

Programme Manager of Artificial Intelligence

Center for Robotics and Neural Systems (CRNS)

School of Engineering, Computing, and Mathematics

Room A307 Portland Square, Drake Circus, PL4 8AA

University of Plymouth, UK
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