15 PhD Degree-Fully Funded at Swansea University, Wales, United Kingdom

Swansea University, Wales, United Kingdom 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 Swansea University, Wales, United Kingdom.

Eligible candidate may Apply as soon as possible.

 

(01) PhD Degree – Fully Funded

PhD position summary/title: COMPUTER SCIENCE: FULLY FUNDED CENSUS LABS AND SWANSEA UNIVERSITY PHD SCHOLARSHIP: MODEL-BASED SECURITY TESTING FOR HARDWARE FAULT INJECTION (RS436)

Model-based security testing has the potential to provide for systematic testing and evaluation of implementations. Security testing of embedded systems (as part of an increasing real-world need for IoT evaluation and certification) is increasingly being adopted in a number of sectors. In collaboration with CENSUS Labs, who are involved in real-world security testing and assurance of systems, this project would develop a formal framework for model-based testing. The model will have to represent the environment, I/O interfaces, internal implementation complexities, and also account for a threat model to represent attacker behaviour. Following from this, a test case generation algorithm would be implemented to account for systematic faults and manipulated sequences to evaluate the system. The project will implement a bespoke test bench, in close collaboration with CENSUS Labs, to automate this tool chain with the ultimate view to assurance against established standards and best practices. The existing configuration provided by embedded systems emulated on an FPGA development environment is a likely test platform for this purpose. A hostile communications environment would be used to emulate attacks established in the literature. Use case from consumer and automotive IoT are likely candidates for early testing against known safety- and liveness-related security properties.

Deadline : 15 November 2023

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(02) PhD Degree – Fully Funded

PhD position summary/title: MATHEMATICS: FULLY FUNDED EPSRC PHD SCHOLARSHIP: NUMERICS OF MEAN-FIELD STOCHASTIC DIFFERENTIAL DELAY EQUATIONS AND APPLICATIONS (RS450)

As so often is the case, the true solutions to stochastic differential delay equations (SDDEs) cannot be expressed explicitly. Hence, analysing the numerical solutions is a common way to get the properties of the true solutions. On the other hand, theories related to stochastic McKean-Vlasov equations (SMVEs) have emerged in many research fields, such as biological systems, chemistry and mean-field games. The distinctive feature of SMVEs is that the coefficients depend on the distributions of state variables. SMVEs are also called distribution dependent stochastic differential equations (SDEs) or mean-field SDEs.

This research project aims to investigate both the qualitative and quantitative properties of mean-field SDDEs driven by Brownian motion and/or fractional Brownian motion, as well as alpha-stable processes. The approach combines probabilistic, analytic and computational methods. The project is ideal for a student who has a solid foundation in probability theory, functional analysis and/or numerical analysis, along with a moderate grasp of measure theory.

Deadline : 13 November 2023

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(03) PhD Degree – Fully Funded

PhD position summary/title: COMPUTER SCIENCE: FULLY FUNDED EPSRC DTP PHD SCHOLARSHIP: COMPUTATIONAL SEMANTICS OF NATURAL LANGUAGE FOR COMPUTATIONAL LAW (RS442)

The PhD candidate will progress state-of-the-art approaches to Computational Semantics of Natural Language with applications in Computational Law. The overall aim is to build a system to accommodate the soft constraints of the Law, which can be violated, rather than have hard constraints (as in Engineering approaches) or post hoc, external adjudication (as currently treated in the courts). A selection from a range of challenging research areas can be addressed: vagueness/open-textured terms, conflicting information and argumentation, exceptions, events/causation, and translations between natural language and the logic. The work is relevant to government as well as service industries of insurance and legal. Links to and integration with data science will also be explored.

Deadline : 13 November 2023

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(04) PhD Degree – Fully Funded

PhD position summary/title: COMPUTER SCIENCE: FULLY FUNDED EPSRC AND SWANSEA UNIVERSITY PHD SCHOLARSHIP: EXPLORING HIGH-RESOLUTION TEMPORAL CORRESPONDENCE IN VIDEO INSTANCE SEGMENTATION (RS432)

Video instance segmentation aims at simultaneous detection, segmentation and tracking of object instances in videos. Given a test video, the task requires not only the masks of all instances of a predefined category set to be labelled but also the instance identities across frames to be associated. Existing methods follow a detection and association paradigm, which essentially performs spatial priors’ estimation and a temporal stitching afterwards. This may hinder VIS in the occlusion and long-term videos. High-resolution (HR) features appear to be helpful to identify small and or occluded objects in static images. Thus, it is interesting to explore this valuable information that may benefit VIS. At the same time, HR feature fusion at temporal level to facilitate the long-term VIS remains open challenge. This project is motivated to design a latent space where HR features of instances can be properly fused at their temporal evolution. The research results will be also applied to related video-based tasks such as optical flow estimation, 3D reconstruction and 3D object detection.

Deadline : 6 November 2023

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(05) PhD Degree – Fully Funded

PhD position summary/title: MATERIALS ENGINEERING: FULLY FUNDED EPSRC AND BRITISH BOARD OF AGRÉMENT PHD SCHOLARSHIP: IMAGE-BASED DIGITAL TESTING FOR FUNCTIONAL CONSTRUCTION MATERIALS (RS441)

Funded by EPSRC and in partnership with the British Board of Agrément, the UK’s major authority for providing product reassurance in the construction industry, this research project will develop new digital testing methods for functional constructional materials with an aim to bring a step-change to product assessment and certification, thereby benefiting the whole construction industry.

Functional construction products (e.g. insulation, damp and sound proofing materials, etc.) are the key elements affecting the safety, efficiency, resilience and comfort of assets, and they have been the primary focus of innovation over time. Traditionally, product assessment is based on accelerated proofing tests. For example, to assess the performance of a product against weathering, a test chamber is equipped with heaters, coolers, UV bulbs and water jets to mimic real-life weather, with the product exposed to magnified conditions for a period of 4-24 weeks. The traditional methods of testing is simple, but time-consuming and expensive, thereby not meeting the demand of rapid innovation and market launch.

Deadline : 22 November 2023

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(06) PhD Degree – Fully Funded

PhD position summary/title: MATERIALS ENGINEERING: FULLY FUNDED UK SHARED PROSPERITY FUND MSC BY RESEARCH SCHOLARSHIP: SUSTAINABLE BIOFUELS TO SUPPORT NETZERO STEELMAKING (RS451)

On the journey to decarbonising energy intensive industries, there are a variety of choices to make. Changing fuel sources has consequences for processes, products and assets. In this study we aim to understand the impact of changing fuel sources in iron oxide sintering for a steelworks to move from fossil carbon to biogenic based sources particularly the volatile materials evolved from said processes. This master’s project will study evolved volatiles and combustion products to understand the levers and impacts of switching fuels. This project will involve surveying the most appropriate raw material sources, chemical characterisation across a variety of techniques and potentially process modelling of the reduction in CO2 emissions from any new processes and as such offers an opportunity to conduct research in a variety of differing fields.

The project will link with Tata Steel which is one of the leading global suppliers of steel products for a wide range of applications, including construction and infrastructure, automotive, packaging and engineering. Sustainability is at the very heart of Tata’s operations and the Company is dedicated to managing operations responsibly and to continuously improving performance.

Deadline : 15 November 2023

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(07) PhD Degree – Fully Funded

PhD position summary/title: MATERIALS ENGINEERING: FULLY FUNDED UK SHARED PROSPERITY FUND MSC BY RESEARCH SCHOLARSHIP: DESIGNER NANOPARTICLES FOR BIOMEDICINE AND ENERGY (RS449)

Nanostructured materials already play a vital role in society. For example, the red lines on a Covid test are nanoscale gold particles. The conventional approach to their production employs solvents and chemicals which present health hazards and environmental challenges. In this project we will exploit breakthroughs in one of two connected areas, according to the expertise of the student:

Development of nanoscale physics-based experimental methods, where Swansea is world leader, to achieve solvent-free synthesis and scale-up of soluble, ligand-capped metal nanoparticles of size 1-100 nm.

Conjugation of the nanoparticles at source with detector molecules chosen to recognise an infectious agent or a biomarker. This will be a completely new method to tether proteins to metal clusters for diagnostics.

Deadline : 15 November 2023

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(08) PhD Degree – Fully Funded

PhD position summary/title: BIOSCIENCES: FULLY FUNDED SWBIO PHD SCHOLARSHIP: UNDERSTANDING THE MOLECULAR BASIS OF SITOPHILUS OLFACTION (RS448)

This is an exciting interdisciplinary opportunity to study the chemical ecology of important cereal pests, the rice weevil (Sitophilus oryzae) and granary weevil (Sitophilus granarius), with a view to developing novel integrated pest management solutions. Rice and cereals are among the most important crops in the world, and weevils of the genus Sitophilus are responsible for significant post‐harvest losses. The use of volatile semiochemicals (behaviour‐modifying ‘information signals’ such as pheromones) to lure pests aways from a crop is a powerful strategy for crop protection; leading to lower pesticide use and so reducing environmental damage as well as contamination of the human food supply chain.

Over the course of this PhD project you will investigate the molecular detail of how Sitophilus weevils detect and interpret chemical signals in their environment. This will involve direct studies of weevil behaviour, insect electrophysiology, synthetic chemistry, analytical chemistry, bioinformatics, computational chemistry and molecular modelling, giving you a broad skill base. Integrated pest management is a vibrant and growing sector with significant employment opportunities in academic, industry, and in regulatory and other government bodies, but the experience and skills you will gain in this project are also directly transferrable to other fields.

Deadline : 4 December 2023

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(09) PhD Degree – Fully Funded

PhD position summary/title: BIOSCIENCES: FULLY FUNDED SWBIO PHD: MICROBIOME-PARASITE RELATIONSHIPS AND DYNAMICS IN LIVESTOCK IN RESPONSE TO PASTURE MANAGEMENT AND ECOLOGICAL STRESSORS (RS447)

The objective of this studentship is to investigate parasites and microbiome-stressor relationships and the methane emissions of cattle kept under different pasture management regimes. The research aims to explore these intricate relationships by:

Identifying potential drivers of cattle infection with gastrointestinal helminths and pathogenic bacteria

Providing first insights into microbiome-parasite interactions under different pasture management regimes and changes in the microbiome over time in response to environmental stressors

Exploring how pasture composition and management affect methane emission and animal health.

Deadline : 4 December 2023

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(10) PhD Degree – Fully Funded

PhD position summary/title: PHYSICS: FULLY FUNDED EPSRC DTP PHD SCHOLARSHIP: POSITRONIUM SPECTROSCOPY (RS444)

Positronium (Ps), being an atomic-like purely leptonic system, attracts a great deal of theoretical studies. The same level of studies have not been achieved experimentally due to the difficulties in forming and probing the Ps. Swansea has one of only a handful of positron beamlines in the world capable of producing Ps in a manner suitable for spectroscopic investigations to compare against the predictions of these theoretical studies. This project will aim to perform experimental spectroscopic investigations of positronium.

Deadline : 13 November 2023

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(11) PhD Degree – Fully Funded

PhD position summary/title: CIVIL ENGINEERING: FULLY FUNDED EPSRC ICASE AND UK DSTL PHD SCHOLARSHIP: TIME VARYING CONTROL OF MULTI-MATERIAL ELECTRO-ACTIVE POLYMER SOFT ROBOTS (RS440)

Building upon cutting-edge work by the group and with the support of EPSRC and the UK Defense, Science and Technology laboratory (DSTL), this PhD project sets out an ambitious research plan which will investigate, with the help of cutting-edge computational modelling and experimental validation, two fundamental aspects: (1) the time-varying response with associated viscoelastic effects in EAP soft robots, in order to predict deformations accurately, and (2) the reliable control in EAP soft robots when accounting for complex internal architecture.

Deadline : 6 December 2023

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(12) PhD Degree – Fully Funded

PhD position summary/title: MECHANICAL ENGINEERING: FULLY FUNDED EPSRC AND UKAEA PHD SCHOLARSHIP: UK ATOMIC ENERGY AUTHORITY CHIMERA FACILITY (RS437)

Swansea University and the UKAEA are collaboratively developing ‘virtual engineering’ capabilities for digital twinning of fusion reactor components. This is in view of enabling better understanding and prediction of fusion reactor systems. For the creation of reliable digital twins, which are typically represented as parameterised mathematical models, three key problems are important:

data integration, i.e., how can measured data be efficiently and reliably integrated into a physics-based model,

the problem of optimal design, i.e., determination of the necessary minimum number of measurements along with their spatial/temporal distributions such that the model reliable,

the problem of data-assimilation, i.e., as more measurements are longitudinally acquired, how can system parameters be dynamically and continuously updated so that the discrepancy between the model output and measurements remains low.

Deadline : 22 November 2023

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(13) PhD Degree – Fully Funded

PhD position summary/title: MECHANICAL ENGINEERING: FULLY FUNDED EPSRC AND SWANSEA PHD: COLLABORATIVE ROBOTICS TECHNOLOGY FOR ASSEMBLY & DISASSEMBLY OF FIDDLY SHAPED OBJECTS IN MANUFACTURING ENVIRONMENT (RS421)

Assembly and disassembly of uncertain shapes, sizes, conditions, and fiddly shaped objects forms a great challenge in manufacturing when considered for automated and robotic processes. This is because it needs a lot of correct identification, dexterity, flexibility, and manoeuvring capabilities of the manipulators. In most cases, it ends-up for manual and tedious processes with limited or no robotics support to human operators. However, this results in increased cost of product repair, end of life decommissioning, and disassembly for replacing parts. This project will focus on understanding the technologies and methods required for flexible and adaptable autonomous assembly and disassembly processes using robotic manipulators associated with humanoid hands and vision system for human-like performance for uncertain shapes, sizes, conditions, and fiddly shaped objects. The project objectives can be summarized as:

Conducting a fundamental investigation into human assembly and disassembly dexterity of fiddly shaped objects using both arms and hand.

Using the knowledge obtained in achieving Objective 1, planning, testing, learning and adaptation strategies for an example assembly and disassembly operations.

Using UR3E/UR5E robots and DLR-HIT II Robot Hands available in the robotics lab to build the infrastructure needed to implement the strategies developed in previous objective 2 in handling complex assembly and disassembly tasks.

Deadline : 15 November 2023

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(14) PhD Degree – Fully Funded

PhD position summary/title: CIVIL ENGINEERING: FULLY FUNDED UKRI & SWANSEA PHD SCHOLARSHIP: DEEP-LEARNING ACCELERATED COMPUTATIONAL FLUID DYNAMIC MODEL FOR POLLUTANT DISPERSION IN URBAN ENVIRONMENT (RS446)

Exposure to hazardous substances from manufacturing, storage and transport poses significant risk to public health and to the environment. Planning control of hazardous substances has been one of the main strategies at different national agencies (e.g. Environmental Agency) to understand the associated risks during the planning phase as well as the operational stage of both new and existing facilities. Apart from extensive networks of physical sensors being deployed island-wide to monitor air quality and pollutants, numerical models of pollutant dispersion for planning and operational purposes have been used. The current industrial numerical approaches are often fast to provide predictions; they are, however, much less accurate due to inherent assumptions and simplifications embedded in those models. There exists a class of higher fidelity methodologies for the prediction of pollutant dispersion using computational fluid dynamic (CFD) approaches. Unfortunately, the CFD-based models are resource intensive and time-consuming to execute; thus, rendering them impractical for industrial usage. The current proposal aims at addressing this gap by developing a fast CFD-based approach for prediction of pollutant dispersion.

Deadline : 13 November 2023

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(15) PhD Degree – Fully Funded

PhD position summary/title: CIVIL ENGINEERING: FULLY FUNDED EPSRC DTP PHD SCHOLARSHIP: INNOVATIVE FLOOD RISK MAPPING TOOL BASED ON MACHINE LEARNING AND HYDRODYNAMIC MODELLING (RS438)

Traditionally, flood risk is mapped using deterministic and simple hydraulic models based on unrealistic assumptions like steady state flow conditions. However, such methods are simplistic and bear large uncertainties as flood events are dynamic, complex, three-dimensional phenomena, and thus rarely comply with these assumptions. Therefore, promoting the ability to credibly map flood risk and improving our understanding of the real risk posed to the public by these events are significant. This project aims to develop a machine learning-based stochastic hydrodynamic modelling for flood risk mapping along with uncertainty assessment. In addition to the conventional flood risk assessment, it can quantify the level of uncertainty associated with flood modelling and assess the impacts of these uncertainties on flood risk. This is vital for reliable design of flood mitigation measures and for resilience of communities at risk of flood incidents.

Deadline : 8 November 2023

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