University of Liverpool, 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 Liverpool, England.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: A 3D-Printed Blood-Brain-Barrier-on-a-Chip for Agrochemical Permeability Studies – CASE Studentship
The blood-brain barrier (BBB) tightly regulates the flow of material between the bloodstream and the brain. One of the big problems faced by a range of sectors, from pharmaceuticals to agrochemicals, is understanding how compounds interact with and cross this barrier. One approach to solving this problem is to design model systems that reproduce the behaviour of the BBB in a lab. Researchers currently rely on 2D in vitro models, which are overly simplistic, or low-throughput animal models, which are ethically questionable and produce data of limited translational relevance. In this project, you will use a 3D printing technique called ‘direct ink writing’ to fabricate a perfusable BBB model (a ‘BBB-on-a-Chip’) that recapitulates human BBB physiology with unprecedented accuracy [1, 2]. You will introduce brain endothelial and parenchymal cells into the printed structures and use confocal fluorescence microscopy, image analysis, and a range of analytical chemistry techniques to study cell behaviour and the ability of your model to reproduce physiological BBB properties. This innovative in vitro tool has the potential to reduce the use of animal models in screening for potential toxicological effects early in the development of novel pesticides supporting chemical design for safety.
Deadline : 12 February 2024
(02) PhD Degree – Fully Funded
PhD position summary/title: Advanced Information Storage
Digital information can be stored in different types of devices depending on the use and how frequently the data need to be accessed. In a typical computer, data that are infrequently accessed are stored in hard disk drives (HDDs). These can be magnetic devices with high storage density in which binary numbers (“0” and “1”) are encoded in the polarity (spin “up” and “down”) of a magnetic medium. Magnetic data storage is cheap and non-volatile, meaning the data persists after power to the device is cut off, but the speed of accessing the data is relatively slow because the read/write procedures involve moving mechanical parts. Data being frequently required, on the other hand, needs to be accessed on a much faster timescale. Memory devices dedicated to this purpose are volatile random-access memories (RAMs) — solid-state electronic devices in which information is electrically stored. The slow non-volatile and fast volatile memories are physically separated in computers (known as von Neumann architecture), resulting in significant latency as the fast processors must wait for the slow data fetching. This has become the key performance bottleneck for the artificial ntelligence (AI) related workloads.
This PhD aims to investigate strategies for designing and producing a universal memory device in micro/nano scale that combines the best of both worlds: low-cost, non-volatile, high-density as a HDD, and robust, fast access as a RAM. This represents a collocation of memory and processing units, and underpins a number of emerging technologies such as MRAM and neuromorphic computing.
intelligence (AI) related workloads.
Deadline : 31 July 2024
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(03) PhD Degree – Fully Funded
PhD position summary/title: An assessment of non-Newtonian flow in laminar and turbulent mixing flow conditions
This fully-funded PhD project provides a unique opportunity to pursue research in advanced experimental fluid mechanics. The project will study the behaviour of non-Newtonian fluids and, in particular, their behaviour in laminar, turbulent and transitional mixing flow conditions. Starting with an analysis of a yield stress fluid contained within a rotating endwall geometry, the project will use start-of-the-art simultaneous 2D3C Particle Image Velocimetry and Planar Laser Induced Fluorescence to study turbulent flow patterns to enhance our understanding of the fundamental flow physics of non-Newtonian fluids in nature and various industrial processes, including the mixing of wastewater sludge and the flow of cement slurries. There will also be the opportunity to develop numerical models of the flows identified using the University of Liverpool high performance computing resource, the parallel Linux cluster, Barkla.
Deadline : 13 February 2024
(04) PhD Degree – Fully Funded
PhD position summary/title: Atmospheric Neutrino Mixing Studies with the Jiangmen Underground Neutrino Observatory (JUNO)
The PhD project will focus on the analysis of atmospheric neutrino data in JUNO and will aim to enhance the JUNO neutrino mass ordering sensitivity, well above the level that could be achieved by 2030 using reactor antineutrinos only. The effort holds the promise of enabling the first unambiguous determination of the mass ordering by the end of this decade. The candidate will focus on atmospheric neutrino selection and kinematic reconstruction using Machine Learning techniques, contribute to the development, tuning and uncertainty evaluations of atmospheric neutrino flux calculations and GENIE-based interaction simulations (http://www.genie-mc.org), and will take a lead role developing a comprehensive, multi-channel JUNO atmospheric neutrino analysis in VALOR (https://valor.pp.rl.ac.uk). The supervisory team has key activities in these areas: Prof. Andreopoulos leads the GENIE and VALOR efforts, and Prof. Lu co-convenes the JUNO neutrino interaction working group.
Deadline : 29 February 2024
(05) PhD Degree – Fully Funded
PhD position summary/title: Beam gas curtain monitor for the High Luminosity LHC
This PhD project will combine numerical studies using available commercial tools, as well as purpose-developed fluid dynamics and Monte Carlo tools to study the gas jet dynamics in various configurations. In addition, machine learning will be applied to optimize data analysis. All results will be benchmarked against data which the student will obtain from measurements using the existing setup at CERN’s Electron Beam Test Stand (EBTS). Furthermore, the integration of the beam monitor into the wider accelerator control system offers exciting prospects for the development of virtual diagnostics that help optimize experimental output.
Deadline : 31 January 2024
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(06) PhD Degree – Fully Funded
PhD position summary/title: Computational Modelling of Nano-Bio-Interfaces
We invite applications for a PhD studentship as part of the Doctoral Training Centre in Biofilms Innovation, Technology and Engineering (BITE). The student will perform computational chemistry research at surfaces and interfaces under the supervision of Dr Matthew Dyer and Prof Rasmita Raval at the University of Liverpool.
Biofilms are communities of micro-organisms that stick to each other within a matrix or at a surface and represent the dominant mode of life for bacteria on earth. Biofilms impact on a ~$5 trillion global economic activity and impact on health and major UK industrial sectors. Understanding and controlling the interaction of molecules with the surfaces of inorganic materials is crucial to gaining control of biofilms and to prevent their formation.
Deadline : 31 January 2024
(07) PhD Degree – Fully Funded
PhD position summary/title: Curve counting via categorification
This project investigates problems in enumerative geometry, which is one of the most fundamental and classical subjects in mathematics. For example, one can ask a question like ‘How many lines pass through two given points in the plane?’. Sometimes the set of all curves satisfying certain geometric properties is finite, but sometimes not. A modern approach to the enumerative geometry is to assign numbers, called `virtual invariants’ to the spaces parametrising all curves we want to count, whether or not they are finite sets. There are several different virtual invariants, and some of them are introduced by physicists in string theory.
Deadline : 31 January 2024
(08) PhD Degree – Fully Funded
PhD position summary/title: Decarbonising global supply chains: tools for trade-off decision-making
This project will develop and validate a conceptual decision intelligence framework and an operational DDSS, to guide stakeholders in making their dynamic trade-off decisions while they are in the process of reconfiguring GSCs (Table 1, Study 1). The developed DDSS will be validated through its application to the critical raw materials (strategic raw materials that are at critical risk of short supply) at the minerals-energy nexus, and to the petrochemical industries GSCs, which have significant scope for reconfiguring to decarbonise by making dynamic trade-off decisions (Table 1, Studies 2 and 3).
Deadline :15 January 2024
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(09) PhD Degree – Fully Funded
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 : 12 January 2024
(10) PhD Degree – Fully Funded
PhD position summary/title: Developing Machine Learning methods to constrain the properties of the Quark-Gluon Plasma
This PhD project will focus on developing novel algorithms and machine learning-based approaches to measurements in heavy-ion collisions, and phenomenological approaches to rigorously compare measurements to models. This project will involve two main research directions:
- The student will work on the ALICE experiment – the LHC experiment dedicated to studying heavy-ion collisions. In particular, they would focus on the measurement of ‘jets’ – collimated sprays of hadrons produced in high-energy particle collisions which provide a unique probe of the QGP as they interact with the QGP at all stages of its evolution. The student will explore the use of Machine Learning as a tool to improve the measurement of jets.
- The student will work on developing and optimising techniques to improve data-model comparisons of heavy-ion data, as part of the JETSCAPE collaboration. Bayesian parameter estimation provides the most natural method for rigorous, multi-observable data-model comparisons, and they will explore and develop new, more efficient approaches for Bayesian analyses, in particular focusing on approaches to optimise posterior sampling.
Deadline : 31 January 2024
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(11) PhD Degree – Fully Funded
PhD position summary/title: Development of Heterogeneous Photocatalysts and Reactors for Production-Scale Photoredox Catalysis (EPSRC iCASE in collaboration with AstraZeneca)
In this project, our aim is to use automated high-throughput experimentation to discover candidate photocatalysts and to develop heterogeneous photocatalyst-compatible photoreactors, integrated with continuous in-line monitoring techniques, to accelerate photochemical reaction development using self-optimisation algorithms and machine learning. The successful implementation of this research will potentially offer major advances in the field of photoredox catalysis and enable scientists to synthesise novel molecules quickly in an efficient, sustainable, and environmentally friendly way. In doing so, this has the potential to impact on society by accelerating drug development and thus the delivery of life-changing medicines to patients.
Deadline : 29 February 2024
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(12) PhD Degree – Fully Funded
PhD position summary/title: Development of proxies for catalytic reactions with high-throughput experimentation and large datasets analysis
This PhD studentship will combine high throughput experimental methods in the synthesis and characterisation of catalysts with automated methods of large dataset analysis to accelerate the discovery of new heterogeneous catalysts for transformations critical to the net-zero economy, such as methanol synthesis from CO2 and green hydrogen production. Libraries of catalysts will be prepared following typical reaction methods, such as impregnation and precipitation, which will be implemented using advanced robotic platforms. The characterisation of products will be done in parallel mode using predominantly diffraction, spectroscopy and thermal analysis techniques. These large-scale characterisation measurements will allow the application of data science methods to build models for catalyst performance. This protocol will generate large datasets in short period of time that will be analysed in batch mode to extract structural, compositional and other properties of the materials. The obtained results will be modelled against the catalytic performance (the catalysis tests will be done at Johnson Matthey) of a selected set of catalysts in order to develop a predictive model, which will be further evaluated and refined by catalysis tests on new sets of samples. The proposed approach allows the exploration of large compositional space of catalysts for key catalytic reactions and enables the development of methods and tools that could be implemented to generate proxy protocols for other catalytic reactions of direct interest to Johnson Matthey. As well as obtaining knowledge and experience in materials synthesis, characterisation and data analysis the student will develop skills in teamwork and scientific communication as the researchers within the team work closely together. The position will appeal to candidates with a strong interest in the synthesis of new materials and catalysis, and in the application of data science and automation methods to chemistry.
Deadline : 29 March 2024
(13) PhD Degree – Fully Funded
PhD position summary/title: Discovery of Functional Inorganic Materials for Net Zero Applications using High-Throughput Synthesis
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 : 1 March 2024
(14) PhD Degree – Fully Funded
PhD position summary/title: Discovery of materials for enhanced PV performance (Ref NSGPVPS2023)
An opportunity for a 3.5 year PhD position supported by NSG Group towards the computational discovery of new materials to enhance the performance of PV devices and forms part of a larger collaboration with NSG around the discovery of new materials for the glass industry.
This PhD project will explore the application of existing computer science methods and algorithms, as well as developing novel ones, to automate the processing of features and their combinations to predict various properties of materials. This may involve developing models to identify new chemistries or regions of the periodic table where these properties may occur, and/or identifying new ways to improve the properties in existing materials.
Deadline : 17 March 2024
(15) PhD Degree – Fully Funded
PhD position summary/title: Discovery of new materials for applications on glass using Mathematical Optimisation and Machine Learning methodologies (Ref NSGPVCS2023)
This PhD project will study and apply existing optimisation methods and propose methods and mechanisms for novel ones. In particular, focus will be given to black-box optimisation methods capable of handling difficult complex problems that are difficult or impossible to model directly. Examples include grid, coordinate and pattern searches, metaheuristics, model-based methods, surrogate models, evolutionary optimisation methods such as genetic algorithms or ones utilising natural gradient and information geometry, and Bayesian optimisation. Many of them relay heavily on the use of various machine learning and statistical mechanisms to adapt to the optimisation landscape and automatically collect data where applicable.
Deadline : 17 March 2024
(16) PhD Degree – Fully Funded
PhD position summary/title: Efficient and accurate Technology Computer-Aided Design simulations with machine learning and their application to develop monolithic CMOS sensors for physics experiments
In this project we propose to develop machine learning methods to support fast and accurate TCAD simulations in a commercial CMOS technology, and to apply the developed methods to guide the design of a real CMOS sensor for physics experiments. The student undertaking this project will collect training data from relevant TCAD simulations, explore a few neural-network models, and choose the most promising one to train and develop a machine learning model. The student will use the developed machine learning tool to run fast and accurate TCAD simulations to input the design of a novel monolithic CMOS sensor with fast-timing.
Deadline : 31 January 2024
(17) PhD Degree – Fully Funded
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 : 16 February 2024
(18) PhD Degree – Fully Funded
PhD position summary/title: Experimental discovery of new Inorganic Materials Towards Net Zero Technologies
New inorganic materials are needed to advance technologies such as batteries for electric vehicles and grid storage, catalysts for biomass conversion or water splitting for hydrogen generation, photovoltaics for solar energy conversion, and to develop our basic scientific understanding of the connection between chemical composition, crystal structure and physical properties. This PhD project is an exciting opportunity for the experimental synthesis and detailed characterisation of new functional inorganic solids, and the targeted application can be aligned with the interests of the successful applicant. The project will combine synthetic solid-state chemistry, advanced structural analysis (crystallography) and measurement of physical properties, with the opportunity to focus on one or more of these aspects during the project. The project will concentrate on the discovery of new bonding types and structures in inorganic solids, as exemplified by materials containing multiple anions [Vasylenko 2021, Gibson 2021, Morscher 2021].
Deadline : 1 March 2024
(19) PhD Degree – Fully Funded
PhD position summary/title: Experimental Discovery of New Ionic Conducting Materials Towards Net-Zero Technologies
The project is based in the Materials Innovation Factory (https://www.liverpool.ac.uk/materials-innovation-factory/) at the University of Liverpool. The project will make use of 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 : 1 March 2024
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(20) PhD Degree – Fully Funded
PhD position summary/title: Exploring how complex glycans shape the human gut microbiota and its interaction with the host
The human gut microbiota is a vast community essential for human health. This community is mainly composed of bacteria and there are as many bacterial cells in our body as there are nucleated human cells. Gut microbiota provides energy, trains and regulates our immune system, and influences our activity through the emerging gut-brain axis.
Composition and diversity of gut microbiota is driven by nutrient availability controlled through the complex carbohydrates produced by the human host and ingested in the diet. Metabolism of these complex carbohydrates by gut bacteria produces short chain fatty acids which act as an energy source for the host, and targets immune cells to reduce inflammation. These short chain fatty acids are also found throughout the body, including in the brain, and consequently have been linked to neuroinflammation and Alzheimer’s disease. The way gut species metabolise complex carbohydrates underpins the effects gut bacteria have on human health. Correct metabolism drives a healthy gut microbiota and a healthy host, whilst improper metabolism can drive dysbiotic gut microbiota and lead to disease.
Deadline : 27 February 2024
(21) PhD Degree – Fully Funded
PhD position summary/title: High volume data processing in real-time infrastructures for the Mu3e experiment
This PhD project will focus on the development of the software for the fast processing and physics analysis on the Mu3e GPU farm. The student will work on the implementation of calibration and alignment procedures on the GPU farm and develop the tolls to apply the required corrections to the data. In parallel they will have a direct involvement in the commissioning of the full online processing system at the experiment at PSI. Benefiting from their deep knowledge of the experiment’s data processing, they will be able to develop online data-analyses to look for new physics beyond the rare muon decay to three electrons, including searching for potentially long-lived axions and dark photons.
Deadline : 31 January 2024
(22) PhD Degree – Fully Funded
PhD position summary/title: Improving core outcome set uptake in trials
Awareness is growing of problems with the choice of outcomes to measure and report in trials, and the waste that this is causing. These include inconsistencies in what and how outcomes are measured across clinical trials; selective reporting of outcomes in some trials; and differences between the outcomes measured in trials and the outcomes that patients consider important. One solution to these problems that is beginning to take hold is for clinical trialists in a particular topic area to measure and report, as a minimum, a core outcome set (COS). A COS is an agreed standardised collection of outcomes that should be measured and reported in a specific area of health.
Deadline : 15 January 2024
(23) PhD Degree – Fully Funded
PhD position summary/title: Indoor Solar Cells
Solar photovoltaics have now become a staple of the power generation mix, deployed on rooftops and in fields around the globe. The technology has now reached a point of maturity where research is focussing on ways to extend it’s use into new and impactful areas of application. Despite sounding faintly ridiculous, there is a burgeoning field focussed on developing high performance solar cells for use indoors or under low illumination conditions1. The need is being driven by the explosion in the number of smart devices used to create the so-called internet-of-things (IoT). There all already in excess of 200 billion IoT devices in operation including various sensors (e.g. temperature, pressure, vibration), tracking tags (GPS, RFID), as well as for multiple control and monitoring applications. The amount of connected devices is likely to exceed a trillion in the coming decade, ~50% of which are anticipated to be indoors and thus subject to artificial light illumination. Developing an efficient and widespread IoT ecosystem has the potential to revolutionise both energy usage and efficiency in a variety of industries and domestic settings. At present IoT devices are predominantly reliant on disposable batteries which need to be produced and replaced, placing a large burden on global resources and additional cost. Switching to solar cell powered devices removes the reliance on disposable battery technology allowing enhanced reliability, removes battery waste and affords longer operational lifetimes for IoT sensor networks. By harvesting ambient light to persistently power individual sensors or nodes from small photovoltaic cells of only a few square centimetres, it enables a new generation of Internet connected devices which can support energy efficiency, real time monitoring or optimised production processes.
Deadline : 12 February 2024
(24) PhD Degree – Fully Funded
PhD position summary/title: Investigating multimorbidity in clinical trials
Clinicians are less likely to prescribe guideline-recommended treatments to people with multiple long-term conditions (multimorbidity) than to people with a single condition [1, 2]. Lack of empirical estimations of treatment effect from RCTs of novel drug treatments have led to uncertainty in treatment recommendations for people with multimorbidity. Participants with comorbidity (the presence of other conditions in addition to specified condition of the RCT, who, by definition, have multimorbidity) are not uncommon in RCTs, but they are under-represented when estimating the treatment effects and drawing treatment guidelines. As the number of people with multimorbidity is rising globally, there is an increasing recognition that clinical guidelines from RCTs should cover patients with multimorbidity [1].
Deadline : 15 January 2024
(25) PhD Degree – Fully Funded
PhD position summary/title: Lifting barriers to Black Academia
This studentship will focus on any field of historical study and any period in which the department has supervisory expertise. The Department of History is part of the School of Histories, Languages & Cultures, one of the largest Schools in the University, exploring culture and society from the origins of humanity and ancient history to modern day politics. We are an interdisciplinary group of historians committed to an engaged approach to the global past. In the 2021 REF exercise 100% of our research was classified as 4* and 3* for Research Environment. We had a 24% increase in 4* research across our outputs, impact, and environment since the last REF. We place particular emphasis on addressing historical injustices through our work on the Holocaust, medical racism, slavery, and colonial and postcolonial violence. From the rise of the far right to climate change, health care, library provision, abortion, religious intolerance and knife crime, we pride ourselves on using historical research to inform key contemporary debates.
Deadline : 25 March 2024
(26) PhD Degree – Fully Funded
PhD position summary/title: Machine Learning methods for lattice field theory and urban studies
We are looking for strong candidates with a background in physics, mathematics or computer science to work on a collaborative PhD project led jointly by the Department of Mathematical Sciences and the School of Architecture at the University of Liverpool. The project focuses on applications of Machine Learning Methods to scientifically different but methodologically close problems in theoretical physics and urban studies.
With guidance and data provided by the experts at the School of Architecture, you will use Machine Learning methods such as deep CNNs and GANs to deal with real-world problems related to classification and generation of street art and urban landscapes. In collaboration with our industrial partner Art Recognition AG (Zurich), you will also have the opportunity to explore machine learning methods for artwork classification, focusing in particular on anomaly detection algorithms. Successful candidate will be very welcome to actively shape these open-ended projects.
Deadline : 31 January 2024
(27) PhD Degree – Fully Funded
PhD position summary/title: Manipulating radical beams to study radical–surface and ion–radical interactions
Radicals are prevalent in gas-phase environments such as the atmosphere, combustion systems, the interstellar medium, and even exhaled breath. However, it is technically challenging to prepare sources of pure gas-phase radicals with tuneable properties. To overcome this issue, we have recently constructed a versatile and innovative “magnetic guide”. The magnetic guide produces a beam of state-selected radicals with continuously tuneable velocity from a mixture of gases (containing radicals, precursor molecules and seed gases). The device is currently being characterised, and will shortly be combined with two existing experiments—an ion trap and a liquid-surface set-up—for the study ion-radical and radical-liquid surface interactions with unprecedented control and precision. In this way, we can examine important gas-phase radical interactions in isolation (i.e. without competing side reactions) for the first time.
Deadline : 12 February 2024
(28) PhD Degree – Fully Funded
PhD position summary/title: Microstructure-flow interplay in 3D printing: linking structure, rheology and printability of bespoke and commercial formulations
In this PhD project, the candidate will expand our fundamental understanding of complex fluids (such as yield stress and elastoviscoplastic fluids) for DIW and other applications using Large Amplitude Oscillatory (LAOS), Fourier Transform (FT) rheology,[4] the Sequence of Physical Processes (SPP) and recovery rheology (strain decomposition approaches). The candidate will investigate the behaviour of a wide range of complex fluids, from formulations for DIW made in our lab (such as ceramics for THz and energy applications) to commercially available materials for a variety of applications. The rheology studies will be complemented with structural techniques where appropriate, for example using rheo-microscopy, fluorescence microscopy and small angle x-ray scattering (SAXS). To complement the experimental aspects of this work, there is additional scope within the project to model complex fluids for DIW using computational fluid dynamics (CFD).
Deadline : 31 March 2024
(29) PhD Degree – Fully Funded
PhD position summary/title: Optical fiber-based RF-breakdown detection and prediction
The QUASAR Group, based at the Cockcroft Institute, in collaboration with the beam instrumentation company D-Beam Ltd, have pioneered the development and commercialization of optical fiber-based beam loss monitors for particle accelerators. During this development it was noted that the device presented a certain sensitivity to the measurement of RF-breakdown events, a commonplace failure mode in RF systems used in accelerator facilities to accelerate particle beams. The signal produced has the potential to provide a means of ongoing live monitoring of the RF source condition and, notably, the possibility to predict failure ahead of time.
Deadline : 31 January 2024
(30) PhD Degree – Fully Funded
PhD position summary/title: Optimised flocculation processes in water treatment
The principal aim of this project is to develop further our understanding of the flocculation process in water treatment, through accurate numerical simulation at laboratory and full scales in order to provide a much-needed step change in flocculator design processes.
The specific project objectives underpinning this aim are to:
1. investigate and determine at lab scale, the precise mechanisms involved in particle agglomeration, breakage and regrowth, and the interactions between turbulence scales and water chemistry for the broadest range of water types.
2. determine the most appropriate method of simulating the flocculation process in water treatment using a modelling strategy that will consider the use of computational fluid dynamics, discrete element modelling and population balance modelling for laboratory scale applications.
3. simulate flocculation processes at full scale and to validate these models with appropriate field data.
4. develop criteria for successful, optimised flocculation for a wide range of raw waters, coagulant types and doses, and flocculators that will be universally applicable and will facilitate a reduced water treatment carbon footprint.
Deadline : 13 February 2024
(31) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship on the History of Race, Health and Medicine
This studentship will focus specifically on any aspect of the history of race, health and medicine from the 18th through to the 21st century, and is part-funded by the Cohen bequest, established by Henry Cohen, 1st Baron Cohen of Birkenhead, who was elected to the chair of medicine at the University of Liverpool in 1934.
The relationship between medicine and race – including medical racism – has recently attracted sustained attention and significant responses from national medical and public health associations, including the American Medical Association, the British Medical Association and the American Public Health Association, with major medical publications connected to these leading organizations publishing special issues on the subject (see: BMJ, AJPH, JAMA). Potential projects might, for example, consider the global circulation of medical knowledge produced in the context of the ‘plantation system’; health care practices and health care experiences of Global Majority groups in a specific historical period or geographic setting; the racialization of bodies, diseases and illnesses; issues around the training and career development of Global Majority staff within medical systems such as the British NHS.
Deadline : 25 March 2024
(32) PhD Degree – Fully Funded
PhD position summary/title: Plasmonic enhancement of single-molecule charge-transport and optoelectronic response.
In this project, we want to systematically study how the charge transport (i.e. conductance) and photonic behaviour (i.e. light-emission) of single-molecule junctions are altered by the nanoelectrode shape. The research programme will entail contribution from device modelling (using FDTD methods), nanofabrication (using thermal scanning probe lithography techniques, tSPL) and optoelectronic measurements (using bespoke mechanically-controlled break-junction equipment, MCBJ).
As part of the studentship the successful candidate will:
· Design nanoelectrodes and computationally model their plasmonic properties.
· Nanofabricate nanoelectrodes using tSPL techniques.
· Fabricate molecular devices with MCBJ techniques and asses their optoelectronic behaviour.
· Contribute to the activities of a diverse research group operating at the chemistry/physics interface
· Gain interdisciplinary experience by being involved in our collaborative network with partners from all corners of the world.
Deadline : 14 February 2024
(33) PhD Degree – Fully Funded
PhD position summary/title: Predicting drug-induced liver injury using circulating free DNA
In this studentship we plan to establish the utility of cfDNA for the detection of clinical drug-induced liver injury (DILI) and provide a deeper mechanistic understanding of the dynamic specificity of cfDNA profiles dependent upon organ and toxic insult. To do this, the successful student will be trained to work with clinical samples and primary human cell models. They will benefit from working in both the academic (University of Liverpool and Edinburgh University) and industrial settings (AstraZeneca, Cambridge) gaining a unique perspective in drug safety science spanning fundamental mechanistic science, with expertise in drug development processes and clinical studies. Overall, with this studentship, we hope to overcome the limitations of dependence on tissue samples or standard blood tests, and expand our ability to detect mechanism-specific drug toxicity in the clinical setting using liquid biopsy.
Deadline : 2 February 2024
(34) PhD Degree – Fully Funded
PhD position summary/title: Preparation and Characterisation of ‘Green’ Photocathodes for the Generation of High-Brightness Electron Beams
This project will focus on development of techniques to manufacture high-performance thin-film photocathode electron sources for particle accelerators, modifying and expanding the deposition equipment and processes as necessary. The use of surfaces modified by techniques such as ion implantation will also be investigates. The goal is to identify the optimum materials and preparation techniques to achieve the highest levels of electron beam brightness, with the lowest intrinsic emittance and the longest operational lifetime.
Deadline : 31 January 2024
(35) PhD Degree – Fully Funded
PhD position summary/title: Probing Death Decisions from Morphogen Gradient Fields
Morphogen gradient scaling is one of the hottest fields in developmental biology at the moment. Scaling is fundamental, explaining how the machinery that controls pattern formation in development (the morphogens) can adapt, so that organs of different sizes show morphological structures which are proportioned. The same developmental machinery can build the leg of a mouse, an elephant or a tumour.
Living systems compete with each other on the basis of available resources, mating or space. It’s not surprising that, within the living individual, the basic functional units of life – the cells – share these competitive attributes1. Cells compete for survival factors, space and also compare fitness traits to win the race of subsistence1-3. Cell Competition was found in Drosophila, where the so-called unfit cells were eliminated from the organ when confronted to the so-called fit cells4. Nowadays, we know that there are several mutations triggering these “battles”, where the ‘unfit cells’ are eliminated from the tissue in the presence of the ‘fit’ ones1, 3-19.
Deadline : 31 March 2024
(36) PhD Degree – Fully Funded
PhD position summary/title: Quantum computing innovation to simulate quantum systems
The emerging technology of quantum computing promises a revolution in numerical simulations of quantum systems for which classical algorithms suffer from computational costs that scale exponentially with the system size. This project will develop and optimize innovative quantum computing techniques to simulate small quantum systems using this rapidly evolving technology.
The project will begin by using existing noisy intermediate-scale quantum (NISQ) devices to simulate small physical systems, such as the lattice-regularized Wess–Zumino model — a supersymmetric quantum field theory that can exhibit spontaneous supersymmetry breaking. As part of this work, you will investigate the capabilities of a variety of NISQ devices, including systems based on binary qubits, d-state qudits, or continuous-variable qumodes, as well as the possibility of hybrid devices.
Deadline : 31 January 2024
(37) PhD Degree – Fully Funded
PhD position summary/title: Reliable modelling of non-Newtonian sludge flows using novel computational fluid dynamics
The project is interdisciplinary in two dimensions because it brings together experiments and simulations as well as solid and fluid mechanics. The integration of concepts and technology across these boundaries brings a level of adventure to the project which is countered by building on well-established research in solid mechanics on quantitative comparisons of measurements and predictions using orthogonal decomposition[i],[ii] leading to validation metrics based on relative error[iii] and assessment of measurement of uncertainty[iv]; and in fluid dynamics using experimental techniques to understand turbulent flow regimes[v],[vi],[vii]. IAEA considers the use of CFD and associated validation data in various nuclear design issues and has identified gaps in verification and validation procedures[viii]. The goal of the project will be to develop techniques that allow volumetric, time-varying, flow data from both measurements and predictions to be represented as feature vectors that can be compared using the validation metrics already established in solid mechanics for dynamic events.
Deadline : 30 June 2024
(38) PhD Degree – Fully Funded
PhD position summary/title: Searches for Axions in Ultra-Peripheral heavy ion collisions
This project is about searching with ALPs using ultra-peripheral Pb—Pb collision (UPC) data recorded with the ATLAS detector at the LHC. In these collisions2, the heavy ions interact electromagnetically without breaking up. They are ideal for the study of photon—photon produced resonances, like ALPs produced by the interaction of two photons. The ALPs then decay to photon—photon pair that can be recorded in the detector. Photon reconstruction and identification in ATLAS has not been optimized for the UPC environment and this opens an excellent opportunity to develop new techniques. A major improvement in the sensitivity of this analysis is expected by studying a photon reconstruction and identification using image analysis with deep neural networks, which will allow us to reconstruct photons with lower transverse momentum and identify them better against backgrounds from electrons or neutral pions than it is now possible using the current algorithms. These techniques combined with the forthcoming LHC heavy ion datasets will enable us to achieve the best possible sensitivity to ALPs leading to a discovery or a most stringent upper limit on their production.
Deadline : 31 January 2024
(39) PhD Degree – Fully Funded
PhD position summary/title: Surface Properties of High Entropy Alloys
The discovery of high entropy alloys (HEA) has attracted much attention in the field of condensed matter physics and material engineering [1]. HEA are alloys formed by at least five elements randomly distributed on crystal lattice sites. They exhibit unexpected properties opening new areas of research in fundamental science and technological applications. Many of the potential applications of HEA such as catalysts and coating materials in transport and aerospace industries are related to surface phenomena. Therefore, an atomic scale understanding of HEA surfaces and interfaces would be vital to optimising these properties. This project deals with characterisation of surface atomic and electronic properties and oxidation behaviour of HEA using ultra-high vacuum-based experimental techniques including X-ray Photoemission Spectroscopy (XPS), Scanning Tunnelling Microscopy (STM), and Low Energy Electron Diffraction (LEED).
Deadline : 12 February 2024
(40) PhD Degree – Fully Funded
PhD position summary/title: Sustainable enantioselective cross-couplings: reaction development and applications in synthesis
The project will involve the development of green and selective enantioselective cross-coupling and heterocyclisation reactions for use in pharmaceutical development and natural product synthesis. The research will encompass synthetic methodology development (including multi-step synthesis), organometallic chemistry, and physical organic chemistry. There is also the option of applying the chemistry in target directed synthesis. For exemplar publications, see: J. Am. Chem. Soc. 2023, DOI: 10.1021/jacs.3c10163; J. Am. Chem. Soc. 2022, 144, 16749
Deadline : 31 March 2024
(41) PhD Degree – Fully Funded
PhD position summary/title: The effect of free radicals on the pathogenesis of Alkaptonuria
We are seeking a motivated researcher to work on a pioneering project investigating the role of oxidative stress in alkaptonuria (AKU) and associated conditions.
AKU is a rare disorder of metabolism caused by congenital deficiency in the enzyme homogentisate 1,2-dioxygenase (HGD), resulting in increased circulating concentrations of homogentisic acid (HGA). Over many years HGA is deposited in connective tissues throughout the body as a dark pigment, which is central to the devastating multiple organ pathology observed in AKU including severe early-onset osteoarthropathy and cardiac disease.
There is growing evidence that oxidative stress is a major part of AKU disease pathophysiology. The Liverpool AKU Research Group has shown that HGA is redox-active, that pigment derived from HGA is a direct source of free-radicals and that anti-oxidant pathways are markedly altered in AKU biofluids and tissues. Oxidative stress associated with lifelong exposure to HGA is thought to account for a number of co-morbidities in AKU, including common diseases such as osteoarthritis, Parkinson’s disease and cataracts; these diseases have markedly increased prevalence in AKU compared with the general population.
Deadline : 31 July 2024
(42) PhD Degree – Fully Funded
PhD position summary/title: Ultra High-Field for Enhanced Solid-State NMR of Materials
This studentship will allow a highly motivated candidate to participate in the development of ultra high-field MAS NMR for materials chemistry offering a unique research profile. The successful applicant will join an international and multidisciplinary research team 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, 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), and expand their research vision and interest by attending (inter)national conferences.
Deadline : 14 January 2024
(43) PhD Degree – Fully Funded
PhD position summary/title: Unlocking precision experiments: Optimizing beam transport and instrumentation at the antimatter experiment AEgIS at CERN
In your project, you will investigate: gas jet targets for studies into eV beam interactions; quantum sensors as single particle detectors; beam quality optimization through realistic 3D start-to-end and trapping simulations; efficient integration of beam and particle diagnostics through simulation and experiment.
Deadline : 31 January 2024
(44) PhD Degree – Fully Funded
PhD position summary/title: Upskilling robotic scientists for long-term laboratory workflows
Physical scientists are progressively using AI-driven robotics and automation to accelerate their experiments and discover materials faster. The COVID-19 pandemic and current climate crisis have created an urgency for these scientists and our societies to transform the way materials are discovered for more resilient, flexible pharmaceutical manufacturing and achieving net zero faster. At the University of Liverpool, the mobile robotic chemist has already outperformed human-level performance in finding clean fuels; however, such platforms are nowhere close to being able to carry out the same vast array of experiments that humans are capable of. Hence, to date, a large amount of laboratory experiments still rely heavily on researchers’ manual, repetitive lab work due to the high level of dexterity and skill required.
Deadline : 31 March 2024
About The University of Liverpool, 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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