Are you holding Master’s degree and ready to elevate your academic journey to the highest level? University of Liverpool, England, has announced a multiple fully funded PhD positions awaiting talented individuals like you. Don’t miss your chance to be part of our vibrant academic community. Explore the exciting PhD positions available and submit your application today!”
Candidates interested in fully funded PhD positions can check the details and may apply as soon as possible.
(01) Fully Funded PhD Position
PhD position summary/title:–A-Eye-Brain-4-Dementia: AI and in silico models in mild cognitive impairment and dementia and beyond
Dementia is a progressive neurodegenerative disease in which patients encounter frequent delays in diagnosis, leading to increased morbidity. There is a major need of biomarkers for the early prediction as acknowledged by the Alzheimer’s Drug Discovery Foundation. The eye is often seen as the ‘window to the brain’ with much effort dedicated recently to predicting disease such as mild cognitive impairment (MCI) and dementia through images of the retinal microcirculation. The eye is closely coupled to the brain through its circulation, with the eye being perfused through a branch off the internal carotid artery that then continues on to the brain. Furthermore, the eye is coupled to the brain neuronally through projection of the CNS into the retina (neuroretina). As such, it is believed that retinal imaging can be used to monitor changes in the brain which has been demonstrated by recent published data. However, whilst the eye is easily imageable down to the micro-scale, the skull around the brain makes imaging much more difficult. Computational models, on the other hand, can simulate the brain circulation and pressure so we know exactly what is happening in the brain in silico. Whilst utilising artificial intelligence (AI) models retinal imaging can help in the diagnosis and prediction of MCI and dementia.
Deadline : 23 September 2024
(02) Fully Funded PhD Position
PhD position summary/title:– Accelerating computational materials discovery with diverse toolsets for verification and optimisation
The discovery of new functional materials to drive technologies for the net zero transition, such as batteries, solar absorbers, rare-earth-free magnets for wind power and a myriad of other unmet needs, is a scientific and societal grand challenge. Recent attempts [1-3] show that reliable automated materials discovery is not currently possible.[4]
Two PhD studentships (1 chemistry, 1 computer science) are available that will tackle the challenge to develop and implement an automated robot-based workflow that will accelerate the materials discovery process. They build on our recent physical science progress in automated synthesis of extended inorganic solids [5] and computer science progress in the diffraction data analysis required to define discovery [6]. The two students will work closely together with a multidisciplinary supervisory team to develop and integrate the methods and tools towards an automated high-throughput workflow that will revolutionise the discovery of functional inorganic materials.
This project, suited to a student with a Computer Science or Mathematics background, will formally define the nature and consequences of the decisions that need to be made in the automated workflow and identify both the optimal combination of existing methods and tools to accelerate discovery and the gaps in capability that currently exist. The student will develop new methods and tools to address those gaps. Their project has the scope to span the entire process from initial suggestion of experimental targets through the autonomous assessment of experimental data produced by the automated workflow to the ultimate definition of experimental success in realising, rather than merely proposing, a new functional material. It offers the student the opportunity to both develop new methods and to participate in implementing them in a new workflow that will change how we find the materials that society will need in the future.
Deadline :31 December 2024
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(03) Fully Funded PhD Position
PhD position summary/title:– Analysis of the role of liver sinusoidal endothelial cells in methotrexate-induced liver toxicity
Liver sinusoidal endothelial cells (LSECs) comprise approximately 50% of the non-parenchymal hepatic cells. They play a vital role in hepatic microcirculation and provide a physiological barrier to the movement of xenobiotics from the bloodstream to hepatic tissue. Methotrexate (MTX) is a chemotherapy and immunosuppressive drug, used at a high dose to treat leukaemia, breast cancer, lung cancer and at a lower dose to manage a variety of autoimmune diseases. The most common adverse effects include hepatotoxicity and blood abnormalities with the mechanism of MTX-induced hepatotoxicity obscure. Our preliminary data from a rat model of MTX injury has shown that MTX can adversely affect liver endothelial cell physiology.
This project will utilise cryopreserved human LSECs to analyse the effect of MTX on endothelial cell physiology, intracellular signalling and gene expression. The project will also utilise a novel 3D multi-cellular liver microtissue composed of primary human hepatocytes, LSECs and human liver fibroblasts to allow analysis of MTX effects on multiple hepatic cells in a more physiologically relevant model.
By understanding the mechanism of MTX induced liver toxicity we aim to ultimately develop potential diagnostic tests and treatment strategies to alleviate MTX toxicity.
Deadline : 29 November 2024
(04) Fully Funded PhD Position
PhD position summary/title:–Developing Approaches to Surveillance for Antimicrobial Resistance (AMR) in the Equine population
Project objectives include conducting and comparing the performance of several surveillance approaches to inform a strategy for the development of a representative national surveillance strategy for commensal AMR in the UK horse population. These will use a number of different data sources and populations of interest including structured sampling via veterinary visited horse populations, a citizen science approach for horse owner recruitment and targeted sampling of populations that might be hard to recruit or underrepresented. These different approaches will be compared to determine their success rate at both recruiting the desired populations, population coverage and feasibility as well as AMR prevalence. xFaeces would be the primary sample collected and commensal E. coli would be the primary sentinel bacterial agent, however we would also archive other Gram negative bacteria on selective media used to screen for AMR. Nasal swabs will also be collected isolation of methicillin-resistant Staphylococcus aureus (MRSA). Isolates will undergo antimicrobial susceptibility testing using microbroth dilution and whole genome sequencing to investigate the AMR genes and strains associated with antimicrobial resistance
Deadline : 1 September 2024
(05) Fully Funded PhD Position
PhD position summary/title:–Developing industrial AI support tools for processing legal cases in medical negligence
Two PhD positions are available within a project that is co-created between the University of Liverpool and Fletchers Solicitors, a Law firm specialising in clinical negligence and personal injury law. As one of the UK’s largest firms in the sector, Fletchers have vast experience from handling legal cases over many years. Each one of their cases is made up of thousands of (unstructured) files – primarily word documents, PDFs and emails. As a result, interpreting their historical caseload and extracting new insight is incredibly challenging, which means that despite their vast experience as a firm, their lawyers often only have their past cases and understanding of the law to guide their decision making and work. Additionally, they spend a lot of time reading or reviewing files, writing drafts, or extracting key information from large bodies of text – as a ‘no win, no fee’ business, spending time only in the ‘right’ places is key to their success.
Deadline : 30 September 2024
(06) Fully Funded PhD Position
PhD position summary/title:–Development of NMR Methods for the Study of Dynamics in Solids
This studentship will allow a highly motivated candidate to participate in the development of dynamics measurements at ultra high-field MAS NMR offering a unique research profile. The successful applicant will join an international and multidisciplinary research team (including other leading high-field NMR laboratories) that will provide complete student training, skills and development, ensuring strong employability. The project is based in the Department of Chemistry at the University of Liverpool, which is an international centre of excellence for the chemistry of advanced materials and leading expertise in NMR, with ample opportunities to work collaboratively. The successful applicant will have access to state-of-the-art local NMR facilities operating at up to 18.8 T (800 MHz 1H frequency), be able to perform experiments at world-leading large scale NMR research facilities including at the UK High-Field Solid-State NMR Facility (that operates NMR systems at 20 T (850 MHz 1H frequency), 23.5 T (1 GHz 1H frequency) and soon 28.2 T) under a wide range of temperatures (100 to 1000 K) and expand their research vision and interest by attending (inter)national conferences.
Deadline : 16 September 2024
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(07) Fully Funded PhD Position
PhD position summary/title:–Discovery of Functional Inorganic Materials for Net Zero Applications using High-Throughput Synthesis
This project will use high-throughput solid state synthesis methods developed in the group (Hampson 2023) to accelerate the discovery of new functional inorganic (oxide) materials for applications towards net zero technologies e.g. ionic conductors, catalysts for electrochemical hydrogen production, transparent conductors. These high-throughput methods will be applied to a variety of materials functionalities depending on the interests of the student and emerging technologies from our industrial collaborators.
The project will involve the preparation of precursor slurries and solutions for dispensing and mixing on robotic platforms before reacting at high temperatures for characterisation on high-throughput powder X-ray diffractometers and other analytical techniques. The project will involve close collaboration with computational chemists to suggest compositional spaces to explore, to predict new structures and aid in the understanding of the properties of the new materials discovered in the arrays using tools developed in the multi-disciplinary EPSRC Programme Grant: “Digital Navigation of Chemical Space for Function” and the Leverhulme Research Centre for Functional Materials Design, that seek to develop a new approach to materials design and discovery, exploiting machine learning and symbolic artificial intelligence, demonstrated by the realisation of new functional inorganic materials. You will thus gain understanding of how the artificial intelligence methods developed in the team accelerate materials discovery, and be able to contribute to the development of these models, which are designed to incorporate human expertise.
Deadline : 31 December 2024
(08) Fully Funded PhD Position
PhD position summary/title:–Electrochemically switchable materials down to the single molecule level
This project will study the electrochemical properties of materials down to the single molecule level and it will investigate how electrochemical (redox state) switching of the molecules can change useful materials properties. This studentship is part of £7.1 million EPSRC-funded Programme grant “Quantum engineering of energy-efficient molecular materials (QMol)”, https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/X026876/1 , which involves the Universities of Lancaster, Liverpool, Oxford and Imperial College, and the group of Professor Richard Nichols at the Department of Chemistry, The University of Liverpool. This PhD project at Liverpool University (Department of Chemistry) will focus on electrochemistry for molecular/organic electronics and thermoelectrics and will include the measurement of the electrochemical and electrical properties of molecular materials from single molecules to self-assembled monolayers and bulk multilayer structures. Techniques to be used in the project include electrochemical methods, scanning tunnelling and atomic force microscopy (STM and AFM), surface spectroscopies and nanofabrication. The QMol Programme Grant aims to realise a new generation of switchable organic/organometallic compounds, with the potential to fulfil societal needs for flexible energy harvesting materials, low-power neuromorphic computing, smart textiles and self-powered patches for healthcare.
Deadline : 30 September 2024
(09) Fully Funded PhD Position
PhD position summary/title:–Fast Algorithms for Huge Dynamic Graphs
Analysing internet-scale data routinely involves graphs with millions of nodes and graphs that change over time. Protecting the UK’s interests necessarily involves processing data related to such dynamic graphs to extract important information pertinent to activities that could pose a threat to the UK.
Therefore, it is important to have scalable algorithms that can extract such information in dynamic contexts. While scalable algorithms do exist in the context of detecting specific known patterns of behaviour in (static and dynamic) graphs, there is also a need for scalable algorithms for detecting anomalous nodes, edges and subgraphs, and anomalous changes to these elements of the graph: anomalies might be indicative of malicious behaviours that have not been seen previously. For example, by detecting these anomalies, we could alert a human analyst that something needs to be investigated.
Many algorithms (and associated approximations), some of which are already scalable in certain contexts, do exist to calculate specific features of nodes, edges, and subgraphs. These algorithms could be used for detecting the anomalies of interest. For example, “betweenness centrality” can be used to identify interesting nodes and scalable algorithms (so long as the average number of edges per node is below a threshold).
This PhD will begin by developing an understanding of the relevance and performance of these existing algorithms at the scales and the dynamic contexts of interest. It will be particularly important to understand how these algorithms can be applied in the context of dynamic graphs and, more specifically, whether the dynamic nature of the problem can be capitalised upon with respect to the development of efficient algorithmic solutions.
Deadline : 13 September 2024
(10) Fully Funded PhD Position
PhD position summary/title:–High power laser development
This PhD project will contribute to a major Ministry of Defence (MoD) research programme intended to develop generation after next technologies for applications in defence and security, and is co-funded by Qinetiq.
The project will focus on creating high-energy, high-repetition-rate lasers. It will involve the student working with optical fibre lasers operating at 1mm and combining the output of these systems using polarisation combination to create one output beam. The project aims to harness the major advantages of chirped pulsed amplifier Yb fibre lasers over other solid-state systems by using combination technologies to increase the low (nJ – mJ) energy output into J level pulses at kHz repetition rates. This performance is unobtainable with current systems and the project involves working at the forefront of laser technology to drive innovative development and performance.
We wish to recruit a PhD candidate to undertake this project and be part of a new MoD/EPSRC Energy Transfer Technology Skills and Training Hub (STH). The main aim of the STH is to train the next generation of leaders in energy transfer technologies relevant for defence and other related applications. The Hub is supported by MoD, Dstl, and UK companies working in the defence and security sector. Each student funded by the Hub will have an industrial partner and have opportunities to work with and train alongside experts from industry. The Hub offers individuals training for both research and industrial career paths.
Deadline : 30 September 2024
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(11) Fully Funded PhD Position
PhD position summary/title:–High-throughput exploration of multicomponent metal organic frameworks (MOFs)
New porous materials are important for advances in key technologies such as carbon dioxide sequestration and storage or catalysts for clean manufacturing. The assembly of multiple metal and organic linkers in the well-defined and complex crystal structures of multicomponent metal organic frameworks (MOFs) will deliver materials with enhanced properties. However, at present we do not have the experimental tools with the scale and speed to efficiently explore the vast chemical space available. This project will harness recent advances in robotics to efficiently explore the discovery of new multicomponent MOFs. The student will design and execute experiments on state-of-the-art robotic synthesis platforms, develop the required measurement approaches to extract and analyse data from the arrays of materials.
Training in robotics, chemistry and structural characterisation will be given. The project will develop protocols to identify materials with potential application gas separation (focusing on capturing carbon dioxide from flue gas and challenging separations of hydrocarbons) and catalysis (transformation of biomass for next-generation clean manufacturing) applications that will focus the large numbers of new materials identified for further detailed exploration. The project is driven by a vision of a future where research scientists will make routine, broad use of robotics as part of the discovery of advanced materials, and thus the project will prepare the student for a wide range of industrial and academic career opportunities.
Deadline : 31 December 2024
(12) Fully Funded PhD Position
PhD position summary/title:–Investigating the Local Mode of Action of Anti-Perspirants using model systems and advanced probing techniques
This EPSRC Case PhD studentship is a collaboration between the University of Liverpool and Unilever to understand the action of personal care products on skin at the localised chemical level.
Personal care products represent a £multi-billion global industry. Such products often require high level chemistry to work synergistically within a complex biological environment. However, the actual action of such products is not understood well due to the difficulty of tracking events within a living system. This project will aim to create a step-change in this field by utilising advanced fabrication to mimic biological systems and then deploying sophisticated techniques to understand the action of anti-perspirants with high chemical and spatial resolution.
The project will fabricate model sweat gland platforms based on recent biological and in-vivo measurement results. The effect of anti-perspirant actives within these mimic systems will be characterised with the advanced surface measurement methods including Atomic Force Microscopy (AFM), Electron Microscopies and localised vibrational techniques of IR and Raman microscopy.
The PhD student will be based at the Department of Chemistry, University of Liverpool and will work within the Open Innovation Hub for Antimicrobial Surfaces and the Surface Science Research Centre.
Deadline : 15 June 2025
(13) Fully Funded PhD Position
PhD position summary/title:–Knowledge-based Design of Dental Surfaces to combat Oral Biofilms
This 4-year BBSRC PhD studentship is a collaboration between University of Liverpool & Unilever R&D.
Oral diseases are among the most common noncommunicable diseases worldwide, affecting an estimated 3.5 billion people. There are major scientific challenges in understanding how protective technologies can be designed and fabricated so that oral biofilms can be controlled to prevent oral diseases. This interdisciplinary project will investigate the protective effect of natural materials that have gained increasing interest, due to their abundant availability and environmentally friendly and biodegradable characteristics. This project will aim to advance this technology by combining advanced imaging and spectroscopic techniques in both Physical Sciences and Life Sciences to understand the how modifications of dental surfaces can be created with precision control on model tooth surfaces and how bacteria and model oral biofilms interact and behave at these surfaces so that their efficacy and mode of action can be understood.
The PhD student will be based at the Department of Chemistry, University of Liverpool and will work within the Open Innovation Hub for Antimicrobial Surfaces and the Surface Science Research Centre.
Deadline : 15 June 2025
(14) Fully Funded PhD Position
PhD position summary/title:–Microbial Induced Electrochemistry at the Local Site and Single Cell Level
Microbial Induced Corrosion (MIC) is a serious economic problem with an estimate worldwide cost of $113 Bn every year. MIC impacts a very wide range of industries, from power plants to construction, and even the health of humans with implants or protheses. While modern research has realised and demonstrated the relevance of microbial corrosion, the processes involved are still poorly understood, and mitigating strategies are still inadequate.
This is not surprising given the variety of electrochemical processes at work in biofilms.
This PhD project brings together expertise in nanoscale surface science and local scale electrochemistry, cell-surface interaction probes, microbiology and imaging across physical and biological sciences to study the electrochemical process that occurs both at the local site and single cell level and at the population level.
The appointed student will gain multidisciplinary skills and expertise in advanced characterisation techniques, including surface spectroscopy, scanning probe microscopy, local electrochemistry and bio-imaging approach, leveraging the unique capabilities at our Open Innovation Hub for Antimicrobial Surfaces, Surface Science Research Centre and the Centre of Cell Imaging, both equipped with state-of-the-art techniques.
Deadline : 15 June 2025
(15) Fully Funded PhD Position
PhD position summary/title:–Non-thermal plasma as a chemical reagent: elucidating mechanism and exploring NTP for pharmaceutically relevant electroreductive reactions
Chemistry depends on electrons, but we cannot yet fully control electrons to deliver precise reactivity. Controlled high-energy electron sources—such as non-thermal plasma (NTP)—could unlock new and selective chemical transformations, but little is known about these states of matter when mixed with reaction media.
We have developed a prototype plasma-microfluidic testing chip and a batch NTP reactor for benchmarking1 and used these to deliver rapid and efficient synthesis of imine macrocycles and metal-organic frameworks. Now, further research is needed to 1) develop the on-chip analysis methods needed to achieve the full potential of these exciting early results and 2) translate this into transformative control of chemical reactivity.
A key missing piece is mechanistic investigations; our prototype has the advantage of minimal evaporation and ready customisation to include analytical equipment. In this PhD, the student will be co-supervised by Prof Anna Slater (flow and supramolecular materials) and Dr Christophe Aissa (organic chemistry, University of Liverpool) and collaborate with Prof James Walsh (plasma physics, University of York), and Dr Timothy Easun (ultrafast vibrational spectroscopy, University of Birmingham) to:
- elucidate the mechanism of the imine condensations that we have established proceed cleanly in 5 minutes under NTP conditions;
- investigate the potential of NTP in electroreductive organic chemistry, focusing initially on reactions important for the pharma industry
- develop methods to probe reaction rates (e.g., radical clock), and hence produce a framework by which NTP reactions can be mechanistically understood, benchmarked against photocatalytic and electrosynthetic methods, and optimized.
Deadline : 10 January 2025
(16) Fully Funded PhD Position
PhD position summary/title:–Real-Time Subsampled Analysis and Recovery for High-Resolution 3D Tomography
3D Imaging, commonly referred to as tomography, is used in many state-of-the-art imaging and characterisation methods, critical to both the medical and engineering sciences. There are several mechanisms used to obtain experimental data, that range from imaging multiple identical structures naturally oriented in different directions, to tilting either the object or illumination and acquiring images of the same structure from multiple different directions.
In all cases, the quality of the final 3D reconstruction is determined by the total number of different projections and the signal to noise of each individual image. This requirement creates numerous experimental challenges; it takes time to acquire each projection, and to achieve high signal/noise each projection requires a high flux of potentially damaging radiation (X-rays, electron, protons, light etc).
Deadline : 13 September 2024
(17) Fully Funded PhD Position
PhD position summary/title:–Understanding interactions between chronic kidney disease and mental health to improve holistic, intelligence-led care
Individually, CKD and mental health conditions account for a significant burden of ill health. The global CKD prevalence was approximately 9%, with regional variations. In the UK around 3 million people in England were living with CKD. In the UK around 20% of UK adults experienced depression or anxiety symptoms. It is predictable to expect a high prevalence of the combination of both chronic conditions. Individuals with CKD are at an increased risk of experiencing mental health conditions compared to the general population. Studies have shown a higher prevalence of conditions such as depression, anxiety, cognitive impairment, and sleep disorders among CKD patients. There is an increasing recognition of the need to consider the mental health implications of CKD and to incorporate mental health screening, assessment, and interventions into the care of CKD patients as a way for healthcare providers to improve the wellbeing and outcomes of individuals living with CKD, with integrated care and tailored interventions. We currently do not know the prevalence of the co-occurrence of specific mental health conditions and CKD, their spatial variation and stratification by different population groups (e.g. socioeconomic). There is a paucity of longitudinal multidimensional data resources that can describe the temporal aspects of disease progression, onset of comorbidities and frequency of interaction with services.
Deadline : 1 September 2024
About The University of Liverpool, England –Official Website
The University of Liverpool (abbreviated UOL; locally known as The Uni of) is a public research university in Liverpool, England. Founded as a college in 1881, it gained its Royal Charter in 1903 with the ability to award degrees, and is also known to be one of the six ‘red brick’ civic universities, the first to be referred to as The Original Red Brick. It comprises three faculties organised into 35 departments and schools. It is a founding member of the Russell Group, the N8 Group for research collaboration and the university management school is triple crown accredited.
Ten Nobel Prize winners are amongst its alumni and past faculty and the university offers more than 230 first degree courses across 103 subjects. Its alumni include the CEOs of GlobalFoundries, ARM Holdings, Tesco, Motorola and The Coca-Cola Company. It was the UK’s first university to establish departments in oceanography, civic design, architecture, and biochemistry (at the Johnston Laboratories). In 2006 the university became the first in the UK to establish an independent university in China, Xi’an Jiaotong-Liverpool University, making it the world’s first Sino-British university. For 2021–22, Liverpool had a turnover of £612.6 million, including £113.6 million from research grants and contracts. It has the seventh-largest endowment of any university in England. Graduates of the university are styled with the post-nominal letters Lpool, to indicate the institution.
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