University of Exeter, England invites online Application for number of Fully Funded PhD Degree at various Departments. We are providing a list of Fully Funded PhD Programs available at University of Exeter, England.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: Nanoscale computer modelling of blush in protective coatings, Natural Sciences – PhD (Funded) Ref: 5069
Aluminium drinks cans are ubiquitous in everyday life to store and transport beverages and other liquids. These cans have an internal protective coating that acts to protect both the internal contents and the can itself. During coating development, simulation tests have been created to increase the speed of iteration and reduce the time required to screen prototypes. One of the failure mechanisms observed during these is an undesirable whitening (or blush) of the polymer film. The work will develop a nanoscale model of a simple coating using state-of-the-art computational approaches including molecular dynamics and free energy calculations to unravel the fundamental science behind the causes of blush. This project crosses multiple traditional disciplines including chemistry, physics, materials science, and computer science and will provide the successful candidate with the opportunity to broaden their scientific knowledge and communication skills across a range of scientific disciplines. This research makes use of the University of Exeter’s high performance computing (HPC) facility, ISCA, and access to regional, national, and international HPC resources as required.
This project is co-funded by AkzoNobel AkzoNobel | AkzoNobel, one of the world’s largest protective coating manufacturers. The successful candidate will work within a multi-disciplinary group and have the opportunity to work closely with the industrial sponsor, forging a close working relationship and industrial contacts.
We are seeking a motivated and resourceful student with an interest in Computational Chemistry/Physics and Materials. A familiarity with programming languages (e.g. python) and HPC environments is desirable. We welcome enquiries from all interested candidates. For informal enquiries please contact Dr Charlie Wand (c.wand[at]exeter.ac.uk).
Deadline : 8th July 2024
(02) PhD Degree – Fully Funded
PhD position summary/title: IMPACT-RISE: Infrastructural surrogate Modelling using Physics-informed And interpretable machine learning for CommuniTy ResIliency and Sustainability Evaluation. PhD (Funded) – Data Science and Artificial Intelligence, Computer Science, and Civil Engineering Ref: 5064
IMPACT-RISE project aims to provide accurate, reliable, and accessible models, thereby playing a pivotal role in fortifying community resilience and sustainability against various hazards. These innovative tools will be instrumental in pinpointing vulnerabilities, optimizing resource distribution, and crafting effective emergency response plans. IMPACT-RISE is grounded in collaborative effort, bringing together a diverse team of specialists in machine learning, civil engineering, and risk analysis. We are committed to align our models with the practical realities and unique challenges of different communities. Through this integrated and cooperative approach, IMPACT-RISE is set to establish new standards in community protection and infrastructure resilience, confronting the diverse challenges of the 21st century with advanced technological solutions and strategic insights.
Deadline : 31st December 2024
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(03) PhD Degree – Fully Funded
PhD position summary/title: ‘Stepping Out’. Creating advanced simulations of scenarios where older adults often fall: paving the way for a step change in falls prevention strategies. Ref: 5071
These PhD studentships will offer the opportunity to join a world-leading falls prevention research team on a prestigious European Advanced Grant project called STEPPING OUT, led by Prof. Sallie Lamb and working with experimental psychologists, biomechanists, physiotherapists and mathematicians within the National Institute of Health and Care Research Exeter Biomedical Research Centre (NIHR Exeter BRC). The successful studentships will also be part of the Dunhill Medical Trust Doctoral Training Programme for Ageing Research, providing additional opportunities for training and development. The projects will be focused on understanding and identifying high risk situations (behaviours and intentions) that can lead to falls, and the strategies (cognitive and motor responses) that older people can implement to correct or avoid those situations (and hence avoid falls). We will use the findings to develop a new generation of fall prevention interventions. The study involves collaboration with the University of Heidelberg and Bologna. The base will be the University of Exeter.
Deadline : 5th July 2024
(04) PhD Degree – Fully Funded
PhD position summary/title: Predictive Modelling of Biomass Loss from Forests (Mathematics, Computer Science) Ref: 5136
Forests are pivotal in regulating the Earth’s climate, sequestering a significant portion of anthropogenic CO2 emissions and maintaining biodiversity (Artaxo et al., 2022; Bonan 2008). However, the resilience of forests is under global threat due to escalating climate change impacts, leading to increased tree mortality and biomass loss (Allen et al., 2010; Hartmann et al., 2022). Understanding and predicting these changes is crucial for forest management and climate mitigation strategies (Anderegg et al. 2020; Millar et al. 2007). Recent advancements in remote sensing, exemplified by high-resolution biomass maps such as MapBiomas (Souza et al. 2020), provide unprecedented data on forests over extended time periods. Coupled with other remote sensing variables (e.g. NDVI, canopy height), these datasets offer a foundation for in-depth analysis of forest dynamics.
The primary challenge for this PhD project lies in accurately identifying and categorising tree mortality events. This requires the integration of diverse data sources, including local carbon and environmental conditions, as well as remotely sensed information. Developing a robust model that can effectively process and learn from these heterogeneous data sources is crucial. The model must not only understand current patterns of biomass loss but also predict future trends in the context of rapidly changing climate conditions.
Deadline : 26th June 2024
(05) PhD Degree – Fully Funded
PhD position summary/title: Geospatial data for property information [Environmental Data Science] Ref: 5137
This PhD project will aim to investigate to what extent we can use AI and spatial data science to create an enhanced property information database analysing a combination of geospatial data that are available online. We will investigate whether openly available images, from either street view or satellites, can be analysed using computer vision techniques to detect properties relevant to buildings and their structure, such as the species of nearby trees, orientation of the building and its state of repair. We will also explore to what extent other data sets can provide contextual information on the history of a building and its changes over time, as well as information about the surroundings, such as built-up density.
Deadline : 26th June 2024
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(06) PhD Degree – Fully Funded
PhD position summary/title: The University of Exeter Business School MRes + PhD Scholarships in Management and Business for Black British researchers Ref: 4551
We are offering a 1-year MRes plus the 3-year doctoral scholarship for Black British researchers. We are keen to receive applications from UK home fee status applicant who identifying as Black (Black or Black British African, Black or Black British Caribbean, Black or Black British other or Mixed Black or Black British)
Deadline : 20th June 2024
(07) PhD Degree – Fully Funded
PhD position summary/title: Uncertainty Quantification in Medical Image Reconstruction, [Computer Science] – PhD (Funded) Ref: 5131
Accurate medical image reconstruction and quality transfer are crucial for diagnosis and analysis. However, the models without calibrated uncertainty estimates might lead to errors in downstream analysis and exhibit low levels of robustness. Estimating the uncertainty in the measurement is vital to making definite, informed conclusions. Especially, it is difficult to make accurate predictions on ambiguous areas and focus boundaries for both models and radiologists, even harder to reach a consensus with multiple annotations. In this PhD programme, we will develop novel uncertainty quantification algorithms with application to image reconstruction and quality transfer in low-field MRI.
Deadline : 14th June 2024
(08) PhD Degree – Fully Funded
PhD position summary/title: What is the Power of Existing UK Moorland and Heathland Vegetation Mosaics to Mitigate Wildfire Spread and Intensity? Ref: 5138
The years 2018-2019 saw the largest individual fires ever experienced in the UK. These fires burned large areas of moorland, and in one case (Winter Hill) took 42 days to extinguish. These events cost more than £20 million, exposed 5 million people across NW England to high levels of particulate pollution, and had major ecological consequences. Summer 2022 saw 15 major wildfire incidents declared (800 separate fires) on a single day in July and we saw the first example of multi-home destruction due to wildfire in the UK. Moorlands and Heathlands are one of the UKs most fire prone landscapes that often carry fires of large, burned area. In some cases, these landscapes have been managed by small, controlled fires or other mechanical means with the aim to leave patchworks of different aged and different height vegetation. This may have the potential to mitigate the spread of fire and fire severity, but this has not been tested. The successful candidate will develop mathematical models that test the ability of different landscape vegetation mosaics to slow or prevent large scale fire spread. This will be based on existing mosaics but will also assess novel mosaics that could improve landscape wildfire resilience. The aim is to build resilience into our moorland and heathland landscapes as climate driven wildfire risk increases into the UK’s future. The position would suit a candidate with a mathematical and geospatial skill set and it would be advantageous to have a background in some aspects of wildfire.
Deadline : 10th June 2024
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(09) PhD Degree – Fully Funded
PhD position summary/title: AI-enhanced dementia prevention: precision risk reduction using large language models, NIHR Funded PhD in Medical Studies Ref: 5100
This PhD project offers a pioneering opportunity to leverage AI, specifically Large Language Models, for dementia prevention and risk reduction. Supervised by a world-class team from the universities of Exeter and Cambridge, the project involves a systematic review, a modified Delphi consensus study, co-development of a custom LLM, and a pilot study in various healthcare settings. It promises significant advancements in dementia risk profiling and reduction, aligning with the NIHR’s vision for innovative, ethical research. This interdisciplinary approach, underpinned by extensive patient and public involvement, presents a unique chance for impactful research in dementia prevention.
Deadline : 10th June 2024
(10) PhD Degree – Fully Funded
PhD position summary/title: The Medical Research Council Centre for Medical Mycology 1+3 MRes-PhD studentships Ref: 4901
The MRC Centre for Medical Mycology (MRC CMM) is a world-leading research centre at the University of Exeter within the Faculty of Health and Life Sciences (HLS) that is helping to tackle the major global threats to human health caused by fungal diseases. The MRC CMM hosts an interdisciplinary group of internationally renowned scientists who study both the host immune response and the fungal pathogen, and is one of the largest such Centres in the world. The mission of the Centre is to facilitate pioneering cross-disciplinary research to substantially advance our understanding of life-threatening fungal infections. These advances will impact patient lives through improved prevention, diagnosis and treatment of fungal diseases in the future.
These four-year studentships start with a 1-year Master of Research (MRes) degree that provides a solid theoretical and practical foundation in fungal infectious disease. This includes one research project on host-pathogen interactions and a second on fungal pathogen biology. On successful completion of the MRes, students then progress to their 3-year PhD, choosing their cross-disciplinary PhD project from a broad selection of peer-reviewed proposals across the Centre’s 5 Research Themes.
Deadline : 9th June 2024
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(11) PhD Degree – Fully Funded
PhD position summary/title: Understanding the evolution of the Nkalonje and Namangali nepheline syenite and carbonatite complexes, Malawi: insights into the formation of a REE-rich carbonatite Ref: 5139
As society increasingly adopts low-carbon energy sources, demand for the raw materials that are critical for this energy transition is rising. Among these, the rare earth elements (REE) are particularly important as they are essential ingredients in high-strength permanent magnets used in wind turbines and most electric vehicles. The largest and highest grade REE deposits are hosted in carbonatites (igneous rocks with >50% carbonate minerals) which have been emplaced at relatively shallow crustal
levels and have undergone sufficient melt differentiation to form REE-enriched ferrocarbonatite.
However, the exact steps in carbonatite evolution remain poorly constrained, in part because of a tendency for most studies to focus on large-scale ore-deposits which, although viable for REE extraction, are typically complexly overprinted by multiple generations of later hydrothermal fluids which mask earlier carbonatite differentiation steps. In this study, the candidate will focus on the Nkalonje and Namangali carbonatites in the Chilwa Alkaline Province of Malawi. Here, rare earth rich
Deadline : 5th June 2024
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(12) PhD Degree – Fully Funded
PhD position summary/title: Preconcentration processes for critical metals in carbonatite complexes: modelling the missing link of early magma reservoirs Ref: 5140
Intrusive carbonatites and associated silicate igneous rocks are highly prospective for a wide range of commodities from metallic rare earth elements, niobium and copper (crucial for the low carbon transition) to minerals apatite and vermiculite (with manufacturing applications). The ultimate origin for these igneous rocks resides in enriched mantle sources, but many processes concentrate the commodities to economic grade (Smith et al., 2016). Multi-stage overprinting by geological processes at relatively shallow levels in the crust obscures the processes that act early to concentrate (or preconcentrate) chemical components. Moreover, experimental petrology thatsimulates evolution in ponded magmas is hindered by the challenge of immiscible separation of carbonated magmatic
components. In contrast, numerical and computational modelling of carbonated magmas has effectively been used to constrain interaction between carbonate and silicate magmatic liquids (Valentini and Moore, 2009). The working hypothesis of this research project is that the geometry of an inflating magma chamber can create the conditions in which a carbonated magmatic horizon can be maintained by fractionation processes (Moore et al., 2022) and therefore lead to the conditions for preconcentration of energy-critical raw materials. However, the morphology and geometry of intrusions in carbonatite complexes is highly variable, and in some case very surprising.
Deadline : 5th June 2024
(13) PhD Degree – Fully Funded
PhD position summary/title: Elvan dykes as sources, fluid pathways and traps of Sn, W, Cu and Li in SW England Ref: 5141
The UK government’s target of net zero greenhouse gas emissions by 2050 will require huge quantities of ‘critical’ raw materials (Lusty et al., 2021), including Sn, W and Li, plus Cu (non-critical), for the production of green technology and other devices, e.g., batteries for electric vehicles. The Cornubian Batholith and associated world-class ore field has a long history of Sn, Cu and W extraction and hosts the largest Li resource in Europe (Gourcerol et al., 2019). There is active exploration ± development for these metals (Cornish Lithium, Cornish Metals, Cornish Tin, Cornwall Resources, Imerys British Lithium) and in every area there are microgranite or porphyry dykes, known locally as ‘elvans’.
The elvans have strike-lengths up to 10 km and widths up to c. 50 m, and have a spatial association with fault-controlled magmatic-hydrothermal lode mineralisation, which can be younger, older or synchronous (Hosking, 1988). Whilst there has been little recent published research on the elvans (e.g., Antipin et al., 2002), there has been considerable new work on the Cornubian Batholith (e.g. Simons et al., 2016, 2017), lamprophyres (e.g. Dijkstra and Hatch, 2019), and the U-Pb cassiterite dating method (e.g. Tapster and Bright, 2020).
The purpose of this field- and laboratory-based study is to determine the mineralogical, mineral chemical and whole-rock geochemical characteristics, relative/absolute ages, and structural context of the elvan dykes and their relationship to batholith construction, vein mineralisation and wall-rock alteration parageneses (e.g., greisen, tourmalinisation, chloritisation). It will help inform exploration models and more sustainable mining practices for Sn, W, Cu and Li.
Deadline : 5th June 2024
(14) PhD Degree – Fully Funded
PhD position summary/title: University of Exeter Faculty of Humanities, Arts and Social Sciences PhD Studentships in Communications, Drama and Film Ref: 5124
1. PhD Film by Practice
This PhD studentship is designed for students wishing to take their filmmaking practice beyond an MA and to integrate their technical and practical skills into more advanced cultural, aesthetic and critical contexts. It is being offered in all film practice subject areas that can be developed through available research supervision in the department. Students produce a work of film practice, which may be a film or films, a screenplay, or other formats of audio-visual work, and a written thesis of up to 40,000 words.
2. PhD in Communications, Drama and Film
This PhD studentship is being offered in the subject areas covered by research and teaching in the department, namely media and communications, drama, film and television. Proposals can be in any single subject area, and we welcome interdisciplinary approaches across those areas. We particularly welcome candidates working on topics related to cultures of the global south. The studentships are open to students wishing to undertake either a standard MPhil/ PhD or an MPhil/ PhD by Performance Practice. Note: this studentship is not open to PhD Film by Practice projects.
Deadline : 3rd June 2024
(15) PhD Degree – Fully Funded
PhD position summary/title: John Oldacre Foundation PhD Studentship in the Sociology and Politics of Agriculture and Food Systems Ref: 5123
We are looking for PhD proposals on any social science issue related to the changing role of agriculture and the countryside relevant to the core research interests of the supervisors. Health and wellbeing of rural communities; health and safety in farming; impact of policy reform; regenerative agriculture; Agricultural markets/trade; Value chains / value capture (e.g., adding value though on-farm processing); Farm labour; Agricultural technology; Knowledge transmission/exchange.
Applications are invited for a PhD studentship (available for study on either a full time or part time basis) in the Centre for Rural Policy Research within the Faculty of Faculty of Humanities, Arts & Social Sciences at the University of Exeter. We are looking for PhD proposals in social science issues related to the changing role of agriculture and the countryside and relevant to the core research interests of the supervisors (see https://sociology.exeter.ac.uk/research/crpr/ for details). We would particularly welcome proposals related to the following themes:
Deadline : 3rd June 2024
(16) PhD Degree – Fully Funded
PhD position summary/title: AI for marine applications: Machine learning and satellite imagery for coastal monitoring. EICDT Studentship Funded PhD Ref: 5130
Estuarine environments are poorly constrained within global carbon assessments like the Global Carbon Budget, which uses globally fixed values. These global assessments are used to guide policy on emissions reductions, hence this limited characterisation of estuarine dynamics results in higher uncertainty and reduced ability to implement legislation. This PhD will exploit high resolution satellite observations, light-weight drones, a low-cost buoy and water sampling to develop spatial assessments of carbon within estuaries. Machine learning will be investigated to intelligently combine these differing observations. Applying these approaches to local estuarine environments could help address the challenge of understanding carbon movement out to sea, quantifying estuarine health, blue carbon storage dynamics and efficacy, or the flux of riverine alkalinity that could enhance or mitigate ocean acidification. Internationally these approaches could equally be applied to study large river systems and their ecosystems, including the Amazon, Congo or those within the Arctic.
Deadline : 3rd June 2024
(17) PhD Degree – Fully Funded
PhD position summary/title: Funded PhD in Primary Care Research Ref: 5097
The Exeter Collaboration for Academic Primary Care (APEx) in the University of Exeter’s Faculty of Health and Life Sciences based at the St Luke’s Campus in Exeter, is inviting applications for a National Institute for Health and Care Research (NIHR) School for Primary Care Research (SPCR) funded PhD studentship to commence in September 2024 or as soon as possible thereafter.
The studentship award provides annual funding to cover Home tuition fees in full, a tax-free stipend of £19,237 per year for 3 years full-time, or pro rata for part-time study, plus a contribution towards research and training costs. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee and no stipend and so they will need to have funding for the remainder of their fees and living expenses from alternative sources. International applicants also need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.
Deadline : 2nd June 2024
(18) PhD Degree – Fully Funded
PhD position summary/title: NERC GW4+ DTP PhD studentship for 2024 Entry. – Improving local weather forecasts for urban areas using machine learning , PhD in Mathematics Ref: 4964
Numerical Weather Prediction (NWP) models produce forecasts that generally perform well at capturing large-scale atmospheric features. However, high-resolution weather models can still exhibit considerable forecast errors, especially over complex terrains such as urban areas. These inaccuracies negatively impact the usefulness of the forecast, and perception of forecast performance by the public. Statistical post-processing techniques can help to reduce forecast errors by training machine learning models on data sets of past forecasts and observations. This project aims to develop and apply novel post-processing techniques to improve weather forecasts, with particular focus on high-impact events over urban areas.
Deadline : 31st May 2024
(19) PhD Degree – Fully Funded
PhD position summary/title: NERC GW4+ DTP PhD studentship for 2024 Entry. – Emergent constraints on future climate extremes , PhD in Mathematics Ref: 4961
A promising method for reducing this uncertainty, the emergent constraint approach, combines empirical relationships found in model ensembles with observations to constrain an unknown sensitivity. The basic idea is to identify an element of the observable climate (𝑋) that varies significantly across the model ensemble, and which exhibits a statistically significant relationship, 𝑓, with variations in some important variable (𝑌) describing the simulated future climate.
There is uncertainty in the mean temperature and precipitation we will experience in the future, however there is even more uncertainty in deviations from the mean. Large deviations are climate extremes such as heat waves and floods. Although these are rare events, this project will use the emergent constraint technique to get a better handle on these future extremes – will heat waves become less common or more frequent leading to more fires?
Deadline : 31st May 2024
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(20) PhD Degree – Fully Funded
PhD position summary/title: NERC GW4+ DTP PhD studentship for 2024 Entry. – Comparative analysis and modelling of cilia motility in a major disease-causing parasite, PhD in Mathematics Ref: 4968
This highly interdisciplinary project will measure, quantify and model the infection process. We will focus on miracidia (which only infects snails), since effective control over the dispersal of snail chemostimulants and infection of the intermediate host will in turn reduce human infections. Specific aims:
How do the miracidia larvae swim? Microscale movement is counter-intuitive and dominated by viscosity rather than inertia. We will measure and quantify miracidia motility (propulsion and ciliary dynamics) over its short life cycle using the model schistosome S. mansoni. Larval swimming will be investigated in the presence of snail-derived peptides and proteins.
What sets snail-parasite specificity? This has been observed anecdotally but not quantified systematically. We will assay and compare motility patterns for distinct parings of snail-parasite species (these are only available from the NHM collection), including using live snail hosts.
How do these chemokinetic responses depend on water temperature, an important consequence of the warming climate. We will combine experimental assays, quantitative analyses, and mathematical modelling, to study how motility depends on temperature, in different species.
Deadline : 31st May 2024
(21) PhD Degree – Fully Funded
PhD position summary/title: NERC GW4+ DTP PhD CASE studentship for 2024 Entry. – Improved extreme climate indices for food security risk analysis , PhD in Mathematics Ref: 4963
1. Quantify the effect of extreme weather events on crop yields and prices, and in particular on the occurrence of market ‘shocks’. This work will use statistical data fusion to coherently merge observations and climate model output on extreme weather events, while also combining these data with existing impacts indices and approaches (including process-based models).
2. Develop improved approaches for assessing extreme event impacts (building on existing approaches and exploring new avenues), and demonstrate them for a small number of representative case studies in agriculture across land uses and geographies.
3. Perform future assessments of impacts, using the improved/developed indices to support risk assessment, resilience and adaptation planning.
The project will provide feedback to the development of climate observations and models, building on the assessment of current capabilities in Task 1. The student will be given opportunities to develop their own ideas and interests within the scope of the project, in discussion with the Lead Supervisor.
Deadline : 31st May 2024
(22) PhD Degree – Fully Funded
PhD position summary/title: Integrating Spontaneous and Coherent Raman Scattering to Advance Analytical Capability Ref: 5032
The project aims to develop a novel technology that merges the complementary capabilities of Raman and coherent Raman scattering microscopy. Raman and coherent Raman scattering (CRS) are both advanced optical analytical techniques used for a wide range of materials and healthcare technologies research. Raman provides detailed molecular information based on the spectral signature of photons inelastically scattered by molecular vibrations. In contrast, CRS microscopy uses ultrafast laser pulses to drive nonlinear light-matter interactions to enhance the signal from a specific vibrational frequency to provide real-time label-free image contrast based on the intensity of a single Raman band.
Deadline : 31st May 2024
(23) PhD Degree – Fully Funded
PhD position summary/title: Deep Learning for multimodal information fusion, [Computer Science] Ref: 5132
This project focuses on the expanding field of multimodal information fusion, which presents enormous potential across a spectrum of applications, including but not limited to object tracking, object detection, medical data processing, robotics, autonomous driving, scene segmentation, pedestrian and cyclist detection, salient object detection, power facility inspection, surveillance, face recognition, crowd counting, and vital sign measurement. The integration of deep learning into multimodal information fusion has recently attracted significant attention, leading to impressive advancements in algorithms, datasets, and benchmarks. The primary aim of this project is to develop innovative, effective, and efficient deep learning algorithms tailored for the intelligent fusion of multimodal information. It will address several critical issues, such as modality alignment, handling of missing modalities, enhancement of computational efficiency, and the ethical use of AI technologies in multimodal information fusion.
Deadline : 31st May 2024
(24) PhD Degree – Fully Funded
PhD position summary/title: Transforming Air Traffic Control: Sequence Prediction and Modelling with Large Language Models Ref: 5128
Recent advances in sequence prediction with large language models have opened up new possibilities in various domains. Building upon these cutting-edge methodologies, this PhD project aims to extend their application to the realm of air traffic control (ATC).
The project seeks to develop an advanced air traffic control agent utilising a unique and rich dataset comprising over 20 years of interactions between air traffic controllers and pilots. The extraordinary ability of these models to generate new, emergent behaviour beyond their training data holds promise for developing an ATC agent that can potentially perform beyond human capabilities. Additionally, it offers opportunities to devise novel strategies for conflict resolution and traffic flow management, leading to improved efficiency and safety in air travel.
Deadline : 30th May 2024
(25) PhD Degree – Fully Funded
PhD position summary/title: Potential of Agrivoltaics in UK Ref: 5125
UK is a country with a population density of 276 people/km2, making it a relatively densely populated area compared to the 62 people/km2 global average. Naturally, this leads to a heightened dependency on the efficient utilisation of land resources. By far the largest method of land use in the UK is for agricultural land, with 71% of the UK’s total land area being used for agricultural purposes. Agricultural activity in the UK satisfied 58% of UK total food consumption in 2021, with the remaining 42% of food consumption being supplied by imports, 23% of which came from EU countries.
However, UKs ambition of achieving 70 GW of installed solar power capacity by 2035 needs significant land. Thus to grow the solar energy market in the UK, land acquisition is inevitable and APV can solve this dilemma. As there is no data available for APV, it is essential to develop and investigate various aspects of APV.
In this work, a scheme will be developed to understand the potential opportunity of agrivoltaics in the UK. New theoretical analysis will be investigate to perform this work.
Deadline : 30th May 2024
(26) PhD Degree – Fully Funded
PhD position summary/title: Royal Navy Musculoskeletal Injury Mitigation Programme, PhD Programme 1: Prospective, longitudinal study of anthropometric factors and lower limb biomechanics during military specific tasks and musculoskeletal injury risk Ref: 5134
This PhD project is part of the Royal Navy Musculoskeletal Injury Mitigation Programme, led by the Institute of Naval Medicine (INM). Musculoskeletal injury (MSKI) and poor health behaviours amongst Armed Forces personnel remain common and persistent problems, impacting employability, and reducing Force operational effectiveness. The Royal Navy MSKI Mitigation Programme (RN MMP), aims to support Sailor and Royal Marines’ health and performance through developing an organisational MSKI risk screening model; and supporting effective and efficient management of rehabilitation and recovery back to Service. To support the scientific evidence-based development, implementation and initial evaluation of the RN MMP, six PhD programmes have been established with the RN MMP Academic Partner University Consortium – comprising the University of Exeter, University of Southampton and University of Bath.
The focus of this PhD project (RN MMP Programme 1) is on the prospective study of anthropometric and biomechanical risk factors associated with injury risk in RN and RM trainees and trained personnel progressing through their Service careers. The successful candidate will be based at the University of Exeter, with data collection at RN and RM establishments. The project will involve the collection of lower limb biomechanical data for functional tasks such as walking, running and jump landings, alongside lower limb anthropometric data. The project will run alongside the other PhD projects of the RN MMP, with data also contributing to a holistic model of lower limb injury risk.
Deadline : 28th May 2024
(27) PhD Degree – Fully Funded
PhD position summary/title: Ultrafast control of valley and spin qubits. Engineering and Physical Research Council (EPSRC) Doctoral Training Partnership – PhD Studentship for September 2024 Entry Ref: 5108
The project will primarily focus on time-resolved measurements using ultrafast laser pulses, to probe the dynamics of valleys and spins. I have recently demonstrated that similar heterostructures based on TMDCs and 2D magnets can lead to exotic phenomena such as all-optical switching via ultrafast charge transfer, and that such materials can be successfully probed in our laboratories in Exeter [5]. Thanks to unique coupling between excitons and magnons in CrSBr [1-3], dynamics of spins can be directly probed in time-resolved measurements, even though the spins form an antiferromagnetic order. Unlike other 2D magnets CrSBr is stable in air, substantially reducing the technological challenges associated with fabrication and making the proposed heterostructures particularly appealing to practical quantum applications. This project aligns with Quantum Technologies theme and if the proposed here approach based upon valley-spin states is to be recognized as the leading concept towards efficient quantum computing, it will have profound effect on the entire quantum industry.
Deadline : 27th May 2024
(28) PhD Degree – Fully Funded
PhD position summary/title: Non-linear quantum optomechanics. University of Exeter Engineering and Physical Research Council (EPSRC) Doctoral Training Partnership – PhD Studentship for September 2024 Entry Ref: 5109
In this project, we will devise a new generation of opto-mechanical devices that can attain the quantum non-linear optomechanical regime. In Fig. 2(a-c) we describe the envisioned device. Two capacitively coupled electrodes enable the interaction between the electrical and the first asymmetric vibrational modes, giving raise to the opto-mechanical couplings 𝐶−1𝑥∝𝑔1𝑥+𝑔2𝑥2.
The fabrication steps of suspended structures will follow similar steps as for suspended graphene [15, 54] and superconducting [55] devices demonstrated at the University of Exeter, see Fig. 2(d-f). In the case of graphene membranes, we will enhance the mechanical quality factor and localize the mechanical mode by exploiting phononic crystals (panel (g) and [12]) with defects (panel (h) and [4]). The Imaging suite and Graphene Centre clean-room facilities will provide access to the state-of-the-art equipment required for the fabrication and preliminary characterization of the envisioned ambitious structures.
Deadline : 27th May 2024
(29) PhD Degree – Fully Funded
PhD position summary/title: Click-based communication in small odontocetes Ref: 5135
Dolphins and porpoises (odontocetes) have complex social systems, but beyond knowing that they use acoustic signals, exactly how they communicate is poorly understood. This PhD is a collaboration between Exeter University and Chelonia Ltd who have developed an instrument that samples sound at 1 million samples per second and identifies what data is worth storing in real time. Acoustic studies of dolphin and porpoises have, hitherto, used recording methods that sample the sound stream at regular intervals. This approach is poorly suited to high frequency sounds like echo-location clicks because the sampling rate (450k samples per second) required to get an un-distorted record is very high and data volumes are consequently very large. In contrast, Chelonia’s F-POD instrument makes the click rate profile of click trains easily accessible, so social and other behaviours that use click rates have suddenly become far more accessible to study than before. This PhD is a data-analysis based project that will use pre-existing data sets and new data collected by partners around the world, and will develop new approaches to quantitatively evaluate evidence for social communication in F-POD data.
Deadline : 27th May 2024
(30) PhD Degree – Fully Funded
PhD position summary/title: 2D-heterostructure devices for nanoscale quantum Sensing. University of Exeter Engineering and Physical Research Council (EPSRC) Doctoral Training Partnership – PhD Studentship for September 2024 Entry Ref: 5114
Precision measurement underpins science and technology, and novel sensors that push the fundamental limits of accuracy and precision are required for applications ranging from nano-electronics to medical imaging. Colour centre defects in the two-dimensional semiconductor hexagonal boron nitride (hBN) have atom-like electronic transitions that can be probed with optical and microwave techniques [1,2], and thanks to a spatial extension on the scale of the atomic lattice, they can provide an exquisite probe of their local environment. This project will develop an integrated microwave and photonic platform to control and investigate spin based sensors in 2D materials [3]. Nanophotonic computational design will be used to optimise the optical interface and the hBN sensing element will be integrated with other 2D materials to develop electrical spin-initialisation and/or readout. The ultimate aim is to build a new generation of sensors with the highest possible sensitivity and spatial resolution, and to apply nuclear magnetic resonance techniques for single-cell analysis, surface chemistry and point-of-care medical analysis.
The project will include a collaboration with the Quantum Materials Team at the National Physical Laboratory (NPL), who will provide access to their precision measurement facilities, including a low-temperature 4-probe scanning tunnelling microscope, which will aid the calibration and qualification of the quantum sensors developed in this project. NPL will also provide access to their Post Graduate Institute for Measurement Science, which will provide additional, industrially relevant training, from world leaders in measurement science.
Deadline : 27th May 2024
About The University of Exeter, England –Official Website
The University of Exeter is a public research university in Exeter, Devon, England, United Kingdom. Its predecessor institutions, St Luke’s College, Exeter School of Science, Exeter School of Art, and the Camborne School of Mines were established in 1838, 1855, 1863, and 1888 respectively. These institutions later formed the University of Exeter after receiving its royal charter in 1955. In post-nominals, the University of Exeter is abbreviated as Exon. (from the Latin Exoniensis), and is the suffix given to honorary and academic degrees from the university.
The university has four campuses: Streatham and St Luke’s (both of which are in Exeter); and Truro and Penryn (both of which are in Cornwall). The university is primarily located in the city of Exeter, Devon, where it is the principal higher education institution. Streatham is the largest campus containing many of the university’s administrative buildings. The Penryn campus is maintained in conjunction with Falmouth University under the Combined Universities in Cornwall (CUC) initiative. The Exeter Streatham Campus Library holds more than 1.2 million physical library resources, including historical journals and special collections.
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