14 Fully Funded PhD Programs at University of Plymouth, England

 14 Fully Funded PhD Programs at University of Plymouth, England

Are you holding Master’s degree and looking for fully funded PhD positions? University of Plymouth, England invites online application for multiple funded PhD Programs / fully funded PhD positions in various research areas.

Candidates interested in fully funded PhD positions can check the details and may apply as soon as possible. Interested and eligible applicants may submit their online application for PhD programs via the University’s Online Application Portal. 

1. Fully Funded PhD Position in Smart nutrient sensor networks using miniaturised optical and electrochemical detection

Summary of PhD Program:

Phosphorus (P) and nitrogen (N) are essential elements for life but excess quantities of fixed nutrients in catchments cause eutrophication, toxicity and affect catchment ecosystem function [1]. Dissolved ammonia (NH3) is a critical chemical parameter required by UK legislation [2], whereas P is often the growth limiting element in catchments, particularly in areas of high N (Nitrate Vulnerable Zones) [3]. Recent legal standards (e.g. Nutrient Neutrality Programme and Environment Act 2021) require nutrient emissions to be determined at catchment scale and concentration limits to be legally enforced. Hence, there is a demand for better spatial and temporal data from water quality monitoring networks [4] and application of emerging technology, including off-the shelf Internet of Things (IoT) sensors and novel miniaturised chemical sensors (nanomaterials, microfluidic spectrophotometric/fluorescence, fiber-optic, microelectrodes) [5-7]. As data flow increases in size and complexity, well designed systems-based approaches are needed to improve cost, efficiency, reduce carbon emissions, minimise computing requirements and support the deployment of sensing systems. 

Application Deadline: 26 April 2024

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2. Fully Funded PhD Position in role of the wind in dispersing and generating plastic pollution

Summary of PhD Program:

This project will combine remotely-sensed, field, and laboratory studies. Field sites will be selected where a clear aeolian contribution can be isolated from hydrological factors, using a combination of UK coastal locations and/or arid/semi-arid regions. The spatial distribution of macroplastics will be described by UAV-based surveys and Machine Learning, supported by field validation. Well-established laboratory-based methodologies (e.g. FT-IR spectroscopy) will be applied to identify the composition of micro-plastics. These will be combined with spatial analysis to address the role of the wind in dispersing, modifying and generating plastics in the natural environment.

Application Deadline: 26 April 2024

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3. Fully Funded PhD Position in Validating portable gamma spectrometry as a tool for mapping spatial patterns in soil organic carbon

Summary of PhD Program:

This project aims to integrate new advances in portable gamma spectrometry technology with emerging and urgent environmental land management needs regarding measurement of soil organic carbon (SOC) (Black et al., 2023). Enhancing SOC stocks is an important step toward meeting climate change adaptation and mitigation needs as well as enhancing soil productivity.

Processes behind building SOC and soil response are complex and quantifying changes in SOC patterns from field to farm scale is an essential step for developing knowledge of optimum management interventions. Convention sampling at scale, however, is expensive and time consuming. Innovation in gamma sensors (Van der Veek, 2021) offers opportunity to deliver rapid, on farm assessment of soil organic carbon (Taylor et al., 2023) but there is dearth of evidence to validate the efficacy of the sensor in range of conditions (different soil types, variability in soil moisture etc).

Application Deadline: 26 April 2024

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 4. Fully Funded PhD Position in Evaluating the role of Big Data in understanding livestock impacts on the upland landscape

Summary of PhD Program:

Upland farming plays a pivotal role in UK upland ecology through existing negative and positive impacts of traditional livestock management but increasingly through incentives to provide ecosystem services (such as improved soil health, biodiversity, carbon sequestration and natural flood management). To evaluate these impacts, fine-scale understanding of livestock movement and behaviour in this environment is essential. In more intensive farm systems, ‘Precision Livestock Farming’ (PLF), the application of Big Data and remote sensing in animal management, is revolutionising the way we understand animals, their interaction with the environment and, crucially, how we farm sustainably. 

Application Deadline: 26 April 2024

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5. Fully Funded PhD Position in Monitoring morphological variability of different gravel barrier typologies

Summary of PhD Program:

The project will involve using novel and multidisciplinary approaches to combine remote sensing observations, data science techniques and numerical modelling for different UK gravel beaches. The student will deploy an emerging observational technology such as 2D LiDAR [7] to monitor high-frequency beachface morphological change and hydrodynamics at six different sites during winter periods and will use open-source water level and wave hindcast data [8] to provide boundary conditions. Tasks will include (i) analysis of the event-scale beachface morphological variability and swash/ overwash processes derived from the 2D LiDAR data using novel analysis techniques, (ii) numerical modelling, and (iii) investigate the linkages between offshore wave climate and runup processes.

Application Deadline: 26 April 2024

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 6. Fully Funded PhD Position in Developing an integrated tool to assess soil health in agricultural settings

Summary of PhD Program:

The health of our soil is integral to the ongoing health of our plant. When managed appropriately, soil can remove and retain large amounts of carbon dioxide from the atmosphere. Soils are also essential for future food security as well as underpinning well-functioning natural terrestrial ecosystems. Some agricultural practices, particularly those where soil is heavily managed through ploughing, grazing, nutrient input and compaction, can act in opposition to longer term carbon storage and productivity goals. In response, there is a strong focus on understanding and maintaining healthy soils in the UK agricultural sector. 

Application Deadline: 26 April 2024

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 7. Fully Funded PhD Position in Monitoring marine biodiversity using AI approaches

Summary of PhD Program:

Imaging platforms are now a key tool in the assessment and monitoring of marine biodiversity. Examples include the use of aerial drones to monitor shores and sea surface populations, use of AUVs and ROVs to survey benthic populations, and the use of static cameras to record behaviours. Processing imagery to extract biologically relevant information is challenging and to date has largely relied on the use of human effort to extract information on identity, abundance, and behaviour of animals. Other key information could be extracted from imagery, for example size-based information (biomass, volume) but this is rarely undertaken due to the technological difficulty, despite biomass being considered as an Essential Ocean Variable. Artificial intelligence and 3D modelling has the potential to significantly advance our capability to monitor marine biodiversity autonomously using imaging platforms, but reliable and integrated workflows to extract information need to be developed and demonstrated. 

Application Deadline: 26 April 2024

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8. Fully Funded PhD Position in Isles of Scilly nematode diseases of scented narcissi: interdisciplinary approaches to diagnosis, characterisation and control

Summary of PhD Program:

Flower growing on the Isles of Scilly (IoS) is of great economic and cultural importance to the Islands. Plant pathogenetic nematodes represent a significant threat to the Isles IoS flower industry: they damage flower bulbs, including locally-grown scented narcissi, and decrease crop quality, making the flowers unsellable. Identification of pathogens is usually performed off-site by specialised personnel, making timely identification of the pests and set up of remedial strategies difficult and potentially expensive. Work by the supervisory team and IoS bulb growers has been carried out to develop simplified disease diagnosis, disease characterisation and development of control strategies. This ResM project will combine molecular disease diagnosis, statistical/mathematical modelling of disease distribution and social science approaches to understand cultural practices impacting disease.

Application Deadline: 31 March 2024

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 9. Fully Funded PhD Position in Developing techniques to deal with large environmental data sets

Summary of PhD Program:

There are now much larger and varied data sets about the environment from, for example: satellite images, results from the internet of things, and even social media posts. In order to monitor the environment and to develop strategies that lead to Net Zero requires that the relevant data is combined together to form big data sets that can be used in machine learning. Large data sets are stored in a variety of different databases, including traditional relational databases and more modern NoSQL databases. To organize the data, the FAIR (Findable, Accessible, Interoperable, Reusable) principles will be used. To process large data sets requires High Performance Clusters (HPC). The University of Plymouth is installing a new HPC system in 2024 that the student will be able to use this system for machine learning with large environmental datasets. 

Application Deadline: 26 April 2024

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10. Fully Funded PhD Position in Understanding the role of the Mas receptor in demyelinating disease and injury

Summary of PhD Program:

Multiple Sclerosis (MS) is a complex neurological disorder with an unknown aetiology and multifaceted pathophysiology. Whilst understanding and therapeutics within this field have been substantial and have improved the lives of many individuals living with MS, there is still an unmet need for interventions that can either protect or repair the nervous system. To develop appropriate therapies that can meet this challenge it is vital that we understand the pathological events following injury and the responses initiated during repair. Our research studies have been focused on components of the renin-angiotensin system (RAS) and have provided significant supporting data to suggest that Mas receptor activation, via therapeutic application of angiotensin 1-7, can provide protection and promote repair following demyelinating injury. However, these studies do not shed light on the role of Mas following a demyelinating injury, whether Mas may have a role in repair and why Mas is expressed on oligodendrocyte lineage cells. Recent research in non-CNS fields of study have suggested that Mas expression is upregulated following injury and may serve to protect or restore damaged tissue. 

Application Deadline: 3 May 2024

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11. Fully Funded PhD Position in Exploring immunosuppression in glioblastoma via high-throughput genomic screens

Summary of PhD Program:

One major reason for treatment failure in glioblastoma is that tumour cells secrete several immunosuppressive factors that alter the functions of immune cells in the tumour microenvironment. Hence, a successful treatment should inhibit the secretion of these immunosuppressive factors and subsequently block the bi-directional communication between the tumour cells and their microenvironment. Identification of genes regulating cell secretion requires a combination of a genetic screening tool (e.g., CRISPR) and a high throughput secretion assay capable of sorting large number of tumour cells based on their secretion patterns. This is not feasible with existing high-throughput cell secretion approaches that typically measure target production rather than secretion. This project leverages a cutting-edge approach, referred to as SECRET (Secretion-Enabled Cell Ranking and Enrichment Technique), to enable high-throughput sorting of cells based on their secretion patterns. We will use SECRET in combination with genome-wide CRISPR-Cas9 screen to identify the druggable regulators of immunosuppression in glioblastoma. Top screen hits will be selected using bioinformatic algorithms. In addition, the therapeutic utility of lead genetic regulators will be assessed through a drug screen. 

Application Deadline: 31 May 2024

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12. Fully Funded PhD Position in Identification of lung cancer patients at higher risk for brain metastasis using microfluidics

Summary of PhD Program:

Up to 55% of the patients with advanced non-small cell lung cancer (NSCLC) develop brain metastases with a median survival of 2–3 and 4–6 months in untreated and treated patients, respectively. Due to the location of metastatic lesions, surgical resection is limited, and chemotherapy is quite ineffective due to the blood brain barrier. It is thus crucial to identify patients at higher risk for brain metastasis at an early stage. Brain metastasis has been ascribed to the presence of subsets of circulating tumour cells (CTCs) that transmigrate through the blood brain barrier and thrive in the brain. No definitive signature genes for brain metastasis have been identified in CTCs from NSCLC due to the lack of validated markers or strategies to isolate these cells. In this project we will deploy a microfluidics-based cell sorting platform to isolate CTCs from a cohort of NSCLC patients with brain metastasis. Isolated CTCs will be subjected to comprehensive gene expression profiling to identify the signature genes of brain metastasis. Consequently, we will develop a microfluidics-based cell profiling platform to analyse the proteins encoded by the signature genes in CTCs collected from NSCLC patients and subsequently identify patients at higher risk for brain metastasis.

Application Deadline: 31 May 2024

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 13. Fully Funded PhD Position in The role of SQSTM1/p62 in Drosophila melanogaster models of neurodegeneration

Summary of PhD Program:

Neurodegenerative disorders including Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia (FTD) are a group of conditions characterised by the progressive degeneration of the structure and function of the nervous system, collectively affecting more than 50 million people worldwide. Neuroinflammation, potentially triggered by infection, proteotoxic and/or oxidative stress, is heavily implicated in the pathogenesis and progression of neurodegenerative disorders.

Macroautophagy, commonly known as autophagy, functions as a lysosomal degradation system responsible for eliminating aberrant cytoplasmic components. Within the autophagy process, SQSTM1/p62 assumes a crucial role by serving as a receptor that facilitates the selective autophagic removal of specific substrates. Currently, the existence of alternative forms of p62 beyond autophagic droplets remains unknown. Mutations in p62 are associated with multiple neurodegenerative diseases, including ALS and FTD. This PhD project aims to investigate the link between p62 and infection, oxidative and proteotoxic stress conditions. Drosophila melanogaster will be used as model organism for investigating the functionality of p62 in in vivo models of neurodegeneration. Furthermore, their role in driving a pro-inflammatory state that promotes neurodegeneration will be determined. 

Application Deadline: 31 March 2024

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 14. Fully Funded PhD Position in Humanities and Business

Summary of PhD Program:

Building on our recent success in REF 2021, the Faculty of Arts, Humanities and Business at the University of Plymouth is making a strategic investment in 6 Fully Funded Collaborative Doctoral Awards (CDAs) and invites talented applicants to submit outstanding PhD research proposals and applications connecting with all our Place-based research in disciplines across the arts, humanities, and social sciences. 

Application Deadline: 25 April 2024

Apply now