PhD studentships
Plymouth Marine Laboratory (PML) works with a number of University partners to train tomorrow’s leaders in Environmental Science. These collaborations, known as Doctoral Training Partnerships (DTPs), offer postgraduate studentships and training across the full range of multidisciplinary environments, helping to enrich the student experience.
Each DTP will create a strong and active community of students that are able – and encouraged – to integrate, work, and learn together. Students will receive in-depth, advanced research training, as well as training in the professional and transferable skills essential in today's economy.
PML is a multidisciplinary, internationally renowned, strategic marine research centre. We have a number of prestigious and exciting opportunities for outstanding students wishing to conduct PhD projects in our areas of research excellence: Earth Observation Science & Applications, Marine Systems Modelling, Marine Ecology and Biodiversity, Marine Biogeochemistry and Observations and Sea and Society.
Quick links:
COCO-VOC studentship opportunity: Sniffing organic gases emitted from atmospheric particulates and understanding their importance
Primary supervisor:
Mingxi Yang, Plymouth Marine Laboratory (miya@pml.ac.uk)
Co-supervisors:
Lucy Carpenter, University of York (lucy.carpenter@york.ac.uk)
Thomas Bell, Plymouth Marine Laboratory (tbe@pml.ac.uk)
Frances Hopkins, Plymouth Marine Laboratory (fhop@pml.ac.uk)
The surface oceans are both a source and sink of a wide range of volatile organic compounds (VOCs). In the marine atmosphere, these gases react with hydroxyl radicals (OH) and determine the reactivity of the atmosphere. VOCs also act as precursors to organic aerosol (atmospheric particulates), which can seed/brighten marine clouds and modulate the amount of the sun’s energy reaching the Earth’s surface…
You will investigate whether light and ozone-mediated reactions on marine aerosol can produce significant amounts of VOCs. Such a production pathway would further our understanding of key components of the Earth System including 1) the marine atmospheric oxidative capacity (Thames et al. 2020), 2) budgets of important trace gases such as glyoxal (Sinreich et al., 2010; Coburn et al., 2014), 3) production of oxygenated organics from heterogeneous reactions occurring on aerosol (e.g. Ziemann, 2005).
Closing date for applications: 17:00 26th January 2025. Proposed start date: after March 2025
PhD studentship with Marine Research Plymouth
Applications are invited for a 3.5-year PhD studentship. The studentship is due to start on 1 October 2025.
The closing date for applications is 12 noon on Monday 6 January 2025.
Understanding the response of marine ecosystems to ocean-based carbon dioxide removal
Second Supervisor (External Lead): Dr Glen Wheeler
Lead Supervisor (DoS): Dr George Littlejohn
Third Supervisor: Professor Helen Findlay
The development of ocean carbon dioxide removal (oCDR) technologies, aimed at helping oceans sequester atmospheric carbon dioxide to prevent excessive warming of our planet, have attracted substantial interest recently. Ocean alkalinity enhancement (OAE) is one such example, where the addition of finely ground mineral rocks to seawater causes carbon dioxide to be drawn down. The project will examine the impact of OAE on marine phytoplankton, testing the resilience of various species to episodes of low carbon dioxide, which will help us understand how, when and where oCDR technologies can be deployed.
Sea to Sky: leveraging AUVs and satellites to determine floating wind impacts on Celtic Sea key ecosystem drivers
Second Supervisor (External Lead): Dr Lilian Lieber (also at UoP)
Lead Supervisor (DoS): Professor Alex Nimmo Smith
Third Supervisor: Dr Peter Miller
The rapid expansion of floating offshore wind (FLOW) infrastructure into deeper, seasonally stratified shelf seas like the Celtic Sea could have profound consequences for ocean dynamics through impacts on ocean fronts, and hence for key ecosystem drivers. Ocean fronts form at the interface of tidally well-mixed and seasonally stratified waters, providing biological hotspots. Despite their recognized importance, frontal habitats remain poorly studied and FLOW impacts are virtually unknown. This project will utilise autonomous underwater vehicles (AUVs) and high-resolution satellite remote sensing to understand FLOW interactions with ocean dynamics in the Celtic Sea, addressing the need for innovative monitoring approaches.
AI-driven biodiversity insight: enhancing underwater ecosystem monitoring through advanced computer vision
Second Supervisor: Professor Kerry Howell (also at UoP)
Lead Supervisor (DoS): Dr Dena Bazazian
Third Supervisor: Dr Pierre Hélaouët
Fourth Supervisor: Dr David Moffat
The health of our oceans is critical to the planet’s overall environmental stability, yet marine biodiversity is under increasing threat from climate change, overfishing, and pollution. Traditional methods of monitoring underwater ecosystems are often limited by challenges such as difficult access and poor visibility. There is an urgent need for innovative approaches that can provide accurate, real-time biodiversity data. This project seeks to harness the power of Artificial Intelligence (AI) and advanced computer vision to transform monitoring of underwater ecosystems. Automating species identification and behaviour analysis will improve the quality and efficiency of biodiversity assessments, providing vital insights to support conservation and sustainable management of marine resources.
ARIES PhD Studentship
Novel Autonomous Techniques to Understand a Volatile Problem: Biological Controls on Seawater Sulfur
Hosted at Plymouth Marine Laboratory
Supervisors
Professor Thomas Bell, Plymouth Marine Laboratory – contact me
Professor Carol Robinson, ENV, UEA
Dr Frances Hopkins, Plymouth Marine Laboratory
Dr Claire Widdicombe, Plymouth Marine Laboratory
The oceans release huge quantities of the gas dimethylsulfide (DMS), which contributes to the formation and growth of atmospheric particles and clouds, reflecting solar radiation. DMS is a key influence on Earth’s climate, with an effect similar in size but opposite in sign to global warming from human CO2 emissions.
DMS in seawater is produced when phytoplankton die and break apart, or by bacteria as they feed on substances plankton excrete. Seawater DMS levels can vary dramatically over small spatial and temporal scales, often spiking during plankton blooms. However, previous technical capabilities and sampling campaigns have not captured these variations in detail or fully understood the dynamics leading to elevated DMS levels. Current models struggle to accurately reproduce DMS observations, and future predictions for plankton and DMS levels remain very uncertain.
NERC GW4+ DTP PhD Studentship for September 2025
Optimal Sensor Placement for Environmental Analysis
NERC GW4+ DTP PhD studentship for September 2025 Entry (Ref: 5414)
Supervisors
Lead Supervisor: David Walker, University of Exeter
Additional Supervisors:
Dr James Clark, Plymouth Marine Laboratory (PML)
Jacqueline Christmas, University of Exeter
Location
Streatham Campus, University of Exeter
The question of where to place environmental sensors is common to all branches of environmental science. Well-established techniques, including those using Gaussian Processes, are often applied to determine optimal placement strategies. A recent study explored the use of a new technique, Convolutional Gaussian Neural Processes (ConvGNPs), for determining optimal air temperature sensor placements in Antarctica (Andersson et al. 2023). This technique offers several advantages, including the ability to fuse multiple data streams, handle missing data effectively, and outperform traditional methodologies.
This project will investigate the application of ConvGNPs for optimal placement of various marine sensors and compare their performance with alternative methods. Applications could include optimizing the placement of wave buoys or new biogeochemical sensors (e.g., measuring pCO2 to determine air-sea flux of carbon dioxide).
Building a Digital Twin Navigating Autonomous Underwater Vehicles to Monitor Water Quality
NERC GW4+ DTP PhD studentship for September 2025 Entry (Ref: 5433)
Supervisors
Lead Supervisor: Dr Jozef Skakala, Plymouth Marine Laboratory
Additional Supervisors:
Prathyush P Menon, University of Exeter, Faculty of Environment, Science and Economy
Dr Juliane Wihsgott, PML, Marine Biogeochemistry and Observations
Autonomous underwater vehicles (AUVs) are establishing themselves as a key source of marine observations. Excitingly, AUVs can be navigated by “intelligent’’ digital-twin (DT) systems based on two-way communication with physical-biogeochemistry models and machine learning components. This maximises the AUV effectiveness and impact by ensuring they target the most interesting/important locations and times, reducing the cost and carbon footprint. The supervisory team is working at the forefront of DT solutions to AUVs, applying them to tracking of phytoplankton blooms (a study: doi.org/10.3389/fmars.2022.1067174) and in ongoing NERC-funded mission tracking harmful algae blooms (HABs) with resulting oxygen depletion (https://www.pml.ac.uk/News/PML-successfully-deploy-a-fleet-of-ocean-robots-to).
However, several assumptions used in those DT systems can be challenged, including those behind design of path-planning algorithms, used sampling setup, merging observations across very different spatio-temporal scales, treatment of biases among different data sources, or neglecting correlations in observations and among model variables. We propose for the student to address those assumptions through a synthetic DT approach where the model output represents “real-world ocean’’ in which virtual AUVs take “samples’’, with all model and observational errors known. Using this approach the student will simulate virtual multi-glider mission experiments, simultaneously tracking HABs and oxygen depletion, finding the optimal DT design to inform future missions.
Statistically Self-Consistent Satellite Data
NERC GW4+ DTP PhD studentship for September 2025 Entry (Ref: 5434)
Supervisors
Lead Supervisor: Dr Peter Edward Land, Plymouth Marine Laboratory, EOSA
Additional Supervisors:
Peter Challenor, University of Exeter, Mathematics and Statistics
Dr Shubha Sathyendranath, PML, EOSA
Processing of satellite data to the mapped images we see everywhere is a complex, multi-step process. Steps are typically undertaken sequentially from raw data to finished product, each making (often implicit) assumptions about the data distribution. From conversion of instrument counts to radiances, through to mapping of multiple overpasses into a daily composite, multiple statistical models are invoked which may not be mutually consistent.
This project will explore ways to reduce these inconsistencies, reprocessing with consistent statistical models. Initial work will focus on creation of composites, the underlying assumption of which is usually that the surface can be represented as a tessellation of uniform map elements at the chosen spatiotemporal resolution, with values assigned by averaging. We can calculate what each sensor would measure if this model were true, then adjust the values accordingly. This optimises extraction of information from multiple sensors with slightly different viewing geometry, with the potential to more effectively ‘see around’ small clouds and other artifacts. This can be tested by using high-resolution satellite data to create ‘virtual’ lower-resolution data, then comparing processing methods. The model can be extended to address challenges like pixel overlap, stray light, out of band response etc.
Assessing the Risk of Consumer Plastics to Marine Ecosystem Services
NERC GW4+ DTP PhD studentship for September 2025 Entry (Ref: 5435)
Supervisors
Lead Supervisor: Dr Samantha Garrard, Plymouth Marine Laboratory, Sea and Society
Additional Supervisors:
Sarah Nelms, University of Exeter, Centre for Ecology and Conservation
Dr Matthew Cole, Plymouth Marine Laboratory, Marine Ecology and Biodiversity
Plastic leakage into the marine environment is a threat to biodiversity and ecosystem services (the benefits derived from nature), yet our current understanding of the risks of plastic products pose is limited. If we are to provide the evidence necessary to improve product sustainability, these risks should be assessed. This may be particularly imperative for consumer plastics given their commonality within the natural environment. In the UK 116 plastic items were found per 100m of beach with consumer plastics the most common items, whilst in Bali, Indonesia over 25 consumer plastics were found per 100m of coral reef.
This PhD aims to identify and assess the risk of consumer plastics to marine ecosystem services. The student will begin by reviewing literature using a systematic approach to collate a broad range of evidence on the impact of these common debris items and highlighting evidence gaps; these environmental implications can then be translated into ecosystem impacts, with the student able to focus on one or several key ecosystem services such as carbon sequestration, food provision, lifecycle maintenance or recreation. The student will then have the opportunity to co-develop research, utilising translation methodologies such as risk assessment, expert elicitation or experimental work.
Marine Ecosystems and Biogeochemistry under Future Climate Change
NERC GW4+ DTP PhD studentship for September 2025 Entry (Ref: 5434)
Supervisors
Lead Supervisor: Dr Lee de Mora, Plymouth Marine Laboratory
Additional Supervisors:
Co-Supervisor: Fanny Monteiro, University of Bristol Geographical Sciences
Co-Supervisor: Gennadi Lessin, PML
Addressing climate change is one of the most important challenges facing humanity. The ocean is already subject to numerous threats linked to climate change, including warming, acidification, habitat loss and more. This project will assess the impact of climate change on the marine ecosystem and its services like carbon sequestration or food production. Using the marine component of existing Earth System Model simulations from the Coupled Model Intercomparison Project (CMIP) and similar products, the candidate will explore questions such as:
How will marine ecosystems recover in a net-zero climate?
How will future international climate change policy impact ocean life?
Does CMIP7 improve representations of marine ecosystems over CMIP6?
Could model comparison tools like ESMValTool be more suitable for marine models?
How well do CMIP models capture the marine ecosystem and associated services and what can be done to mitigate negative impacts?
Can climate projections be used to define sustainable Marine Protected Areas?
What model development & sensitivity experiments are needed to improve marine ecosystem models?
The candidate will work in collaboration with international experts in climate change impact and marine ecosystem modelling and will be given all the tools and knowledge needed to independently generate and communicate climate change research.