{"id":4014,"date":"2023-08-27T05:00:37","date_gmt":"2023-08-27T05:00:37","guid":{"rendered":"https:\/\/fellowshipbard.com\/?p=4014"},"modified":"2023-08-24T23:03:42","modified_gmt":"2023-08-24T23:03:42","slug":"37-fully-funded-phd-programs-at-university-of-liverpool","status":"publish","type":"post","link":"https:\/\/fellowshipbard.com\/37-fully-funded-phd-programs-at-university-of-liverpool\/","title":{"rendered":"37 Fully Funded PhD Programs at University of Liverpool, England"},"content":{"rendered":"
Are you holding Master\u2019s degree and looking for fully funded PhD positions? University of Liverpool, England invites online application for multiple funded PhD Programs \/ fully funded PhD positions in various research areas.<\/span><\/p>\n Candidates interested in fully funded PhD positions can check the details and may apply as soon as possible. Interested and eligible applicants may submit their online application for PhD programs via the University\u2019s Online Application Portal.\u00a0<\/span><\/p>\n This project seeks to understand the molecular mechanisms by which gut bacteria metabolise complex carbohydrates and how this influences their interaction with the host. You will employ an integrated strategy of protein biochemistry, bacterial genetics, metabolomics, and tissue culture to uncover the fundamentals of these metabolic processes seeking how they can be exploited to maximise human health and treat diseases.<\/span><\/p>\n Apply now<\/strong><\/span><\/a><\/p>\n This project will compare the gene expression profiles of parasites and related non-parasites under various cellular conditions using state-of-the-art transcriptomic and proteomic methods. The data we produce will be used to estimate gene co-expression networks to test the hypothesis that gene regulation has become simpler and less connected in parasites. There are four stages. (1) Transcriptomic and proteomic analysis of stress responses in different parasites and their free-living relatives; (2) Identifying protein-protein interactions involved in stress responses. (3) Gene knock-out of key stress responders in different species. (4) Gene replacement to explore evolutionary hypotheses of parasite gene loss.<\/span><\/p>\n Apply now<\/strong><\/span><\/a><\/p>\n <\/p>\n Follow FellowshipBard for daily updates! <\/span><\/strong><\/span><\/p>\n Facebook<\/span><\/strong><\/a><\/span><\/p>\n Twitter<\/span><\/strong><\/a><\/span><\/p>\n Linkedin<\/span><\/strong><\/a><\/span><\/p>\n Low and zero thermal expansion materials are used in many industries where size stability under high temperatures is critical e.g., aerospace, precision manufacturing, sensors. New classes of material are needed to meet intensifying future demands. There are considerable barriers to discovering the required materials. The underlying physics is complex and difficult to predict from first principles, and the space of possible materials is large and equally complex, especially when a combination of properties is needed, i.e., in this case zero thermal expansion and high machinability and durability. Machine learning methods have been successfully applied to many complex problems, and recent work has demonstrated such methods may also be viable to predict new functional materials with desirable properties.<\/span><\/p>\n Apply now<\/strong><\/span><\/a><\/p>\n This project aims to develop new materials for optoelectronic applications on glass to contribute to the net zero agenda. New materials are required to maintain the pace of efficiency and performance improvements in thin film PV devices, energy saving glazing, electronic displays, lighting and other emerging markets. Previous work in collaboration with NSG has used computational chemistry and deep (machine) learning to predict new material compositions with high optical transparency and high electrical conductivity.<\/span><\/p>\n Apply now<\/strong><\/span><\/a><\/p>\n <\/p>\n 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.<\/span><\/p>\n Apply now<\/strong><\/span><\/a><\/p>\n <\/p>\n 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.<\/span><\/p>\n Apply now<\/strong><\/span><\/a><\/p>\n <\/p>\n The project will combine synthetic solid-state chemistry, advanced structural analysis and measurement of physical and electrochemical properties of new lithium solid electrolytes, enabling the successful candidate to develop a diverse experimental skillset in materials chemistry and battery chemistry. The focus will be on the discovery of new materials and structures with enhanced performance, accelerated by working with computational design experts. Owing to the multi-faceted nature of this dynamic project, the student will work closely with computer scientists, inorganic (electro)chemists, physicists, engineers, and material scientists, as part of the EPSRC Programme Grant \u201cDigital navigation of chemical space for function\u201d, to discover new solid electrolytes for all-solid-state Li metal batteries.<\/span><\/p>\n Apply now<\/strong><\/span><\/a><\/p>\n 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. <\/span><\/p>\n Apply now<\/strong><\/span><\/a><\/p>\n <\/p>\n This project aims to design and develop a Mobile Robotic System which will autonomously and safely navigate within an agriculture setting to monitor and respond to key sensor data of moisture and temperature to optimise particular farming tasks to support farmers and reduce risks of contamination and\/or infection. Developing an autonomous system capable of operating in harsh changeable environment such as in agriculture settings, is a significant research challenge. The dynamic cluttered setting and the uneven and changing terrain are major challenges to an autonomous vehicle to safely map and navigate its way around a farm and complete set tasks.<\/span><\/p>\n Apply now<\/strong><\/span><\/a><\/p>\n This project will develop novel validation methods to build confidence in computational models that predict performance of engineering structures. Computational models are vital for exploring and developing future infrastructure, such as zero-emission aircraft or supplying clean energy. Before a virtual design is brought to life, its computational models must be validated to demonstrate confidence in the safety and performance of the design. The confidence in the models is particularly important when they are used to inform decisions that could have socio-economic consequences.<\/span><\/p>\n Apply now<\/strong><\/span><\/a><\/p>\n Are you a motivated student with a strong interest in biomaterials and tissue engineering and applying this to treat a specific eye disease? Then look no further! This PhD project focuses on developing a new conjunctival substitute based on artificial materials that mimic tissue structures on which we can grow conjunctival surface epithelium. This artificial conjunctiva has the potential to overcome the limitations of current reconstructive techniques and will have impact in preventing patient suffering including blindness, pain and double vision. <\/span><\/p>\n1. Fully Funded PhD Position in Biological and Medical Sciences<\/strong><\/span><\/h1>\n
Summary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 27 February 2024<\/span><\/span><\/h3>\n
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2. <\/strong><\/span>Fully Funded PhD Position in gene expression regulation in eukaryotic parasites<\/strong><\/span><\/h1>\n
Summary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 27 August 2023<\/span><\/span><\/h3>\n
3. <\/strong><\/span>Fully Funded PhD Position in Chemical Sciences<\/strong><\/span><\/h1>\n
Summary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 17 March 2024<\/span><\/span><\/h3>\n
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4. <\/strong><\/span>Fully Funded PhD Position in Physical Sciences<\/strong><\/span><\/h1>\n
Summary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 31 December 2023<\/span><\/span><\/h3>\n
5. <\/strong><\/span>Fully Funded PhD Position in Maths and Computing<\/strong><\/span><\/h1>\n
Summary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 17 March 2024<\/span><\/span><\/h3>\n
6. <\/strong><\/span>Fully Funded PhD Position in Chemical Sciences<\/strong><\/span><\/h1>\n
Summary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 17 March 2024<\/span><\/span><\/h3>\n
7. <\/strong><\/span>Fully Funded PhD Position in Chemical Sciences<\/strong><\/span><\/h1>\n
Summary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 31 December 2023<\/span><\/span><\/h3>\n
10 Best AI Cover Letter Builders<\/a><\/span><\/strong><\/span><\/h3>\n
8. <\/strong><\/span>Fully Funded PhD Position in Chemical Sciences<\/strong><\/span><\/h1>\n
Summary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 29 March 2024<\/span><\/span><\/h3>\n
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9. <\/strong><\/span>Fully Funded PhD Position in Engineering and Planning<\/strong><\/span><\/h1>\n
Summary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 31 October 2023<\/span><\/span><\/h3>\n
\n10. <\/strong><\/span>Fully Funded PhD Position in Engineering and Planning<\/strong><\/span><\/h1>\nSummary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 31 December 2023<\/span><\/span><\/h3>\n
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11. <\/strong><\/span>Fully Funded PhD Position in Biological and Medical Sciences<\/strong><\/span><\/h1>\n
Summary of PhD Program:<\/strong><\/span><\/h2>\n
Application Deadline:<\/strong> 21 March 2024<\/span><\/span><\/h3>\n