Funded Postgraduate Research Scholarships
Current Postgraduate Funded Research Master's and PhD Scholarships are listed below...
Applicants interested in applying for a research masters or PhD should also check individual Faculty webpages for information on current research projects.
| Project(s) | Development of algorithms and methods for single cell omics data analysis (School of Medicine) Rapid advancements in single cell ‘omics technology allow measurement of DNA, mRNA and proteins in thousands of individuals cells in a single tissue biopsy. Data sets are sparse, high dimensional and frequently contain measurements from over 1 million cells. The Culhane lab are developing computational and statistical tools to analyze these data. This project will develop approaches for dimension reduction of sparse, single cell ‘omics data, with a focus on data integration and pathway analyses. The project will leverage existing R and Bioconductor packages developed by the Culhane lab and develop new Bioconductor packages and methods for analysis of spatial, single cell omics data. |
| Faculty | Education and Health Sciences |
| Entry Requirements | Applicants should have a first or upper second-class honours degree at undergraduate or master’s level or equivalent in bioinformatics, biostatistics, math, engineering, computer science or a related discipline. |
| Funding/Stipend | Stipend of €16,000 tax free per annum, EU tuition fees covered. Non-EU students may have to pay balance of full fees. |
| Contact & How to Apply | |
| Additional Information | Culhane Lab Studentship Development of algorithms and methods for single cell omics data analysis Scientific curiosity and a commitment to work in an open science team environment are important to our goals. The successful candidate will have strong communication skills, be highly motivated, and will be able to think critically to solve a problem. Applicants should have a first or upper second-class honours degree at undergraduate or master’s level or equivalent in bioinformatics, biostatistics, math, engineering, computer science or a related discipline. Applicants from non-traditional backgrounds are encouraged to apply. The applicant should have experience in at least one computer language, be excited to write R/Bioconductor code, and most of all really enjoy matrix algebra and algorithm development. Experience in analysis of spatial data (eg GIS data, ARCGIS, shapefiles, etc), optimizing code for high performance computing, cloud computing, or benchmarking algorithms would be a distinct advantage. Meng C, Zeleznik OA, Thallinger GG, Kuster B, Gholami AM Culhane AC*, Dimension reduction techniques for the integrative analysis of multi-omics data. Special issue on Computational Systems Biomedicine in Briefings in Bioinformatics 2016 Mar 11. pii: bbv108. |
| Project(s) | Funded PhD Project in Molecular Modelling at the Bernal Institute at University of Limerick. |
| Faculty | Science and Engineering |
| Entry Requirements | Honours BSc or MSc in chemistry, physics or related area, with strong interest in molecular modelling |
| Funding/Stipend | EU applicants will be eligible for a full award paying fees and maintenance at standard rates. The stipend rates for 2020/21 studentships are €5,500 EU fees, stipend €18,500 per annum. |
| Contact & How to Apply | |
| Additional Information | Additional Information Applications are now open for a fully funded PhD project in Molecular Modelling at the Bernal Institute at University of Limerick. Talented, ambitious, and highly-motivated students with a good honours degree in Chemistry, Physics, Biochemistry or related areas are encouraged to apply.
The successful candidate will be trained in molecular modelling in the vibrant, cutting-edge research group of Prof Damien Thompson, working in a diverse, multidisplinary team of postdoctoral fellows and PhD students. The position is available immediately or as soon as the selected candidate is available to start, and preference will be given to candidates with demonstrated experience and/or strong interest in molecular modelling.
Current projects in the group address societal grand challenges in sustainability and health (for more, see https://sspc.ie/modelling/), and include design of molecular memories (1), energy harvesters (2) and drug targets for neurodegenerative disease (3). If you would like to grow and challenge yourself in a supportive, stimulating research environment then we would love to hear from you! Please send your CV and letter of introduction to damien.thompson@ul.ie
1. Decision trees within a molecular memristor. S Goswami et al. 2021. Nature 597, 51 2. Control of piezoelectricity in amino acids by supramolecular packing. S Guerin et al. 2018. Nature Materials 17, 180 3. Complete aggregation pathway of amyloid β (1-40) and (1-42) resolved on an atomically clean interface. PN Nirmalraj et al. 2020. Science Advances 6, eaaz6014
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| Project(s) | SFI Centre for Research Training (CRT) in Artificial Intelligence: Fully Funded PhD positions (30-35 posts) across 5 Irish Universities Artificial Intelligence (AI) plays a significant role in the world today. Its impact is transformational, and it is disrupting society and industry alike. Over the last decade major advances have been achieved due to the availability of vast amounts of digital data, the availability of powerful computing architectures, and advances in AI techniques, such as machine learning.
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| Faculty | Science and Engineering |
| Entry Requirements | Applicants should hold a 2.1 or higher honours undergraduate degree or Masters degree in Computer Science, Computer Engineering, Data Analytics, Mathematics, Statistics, or related areas. Ideally applicants will be able to demonstrate experience in both theoretical and software engineering skills, with a keen interest in Algorithms, Artificial Intelligence, and related areas. We are especially interested in candidates with knowledge of Artificial Intelligence, Machine Learning, Constraint Programming, Operations Research, and Wireless Sensors. Candidates are required to provide evidence of English language ability as per local University guidelines. UCC: https://www.ucc.ie/en/study/comparison/english/postgraduate/ NUIG: http://www.nuigalway.ie/international-students/entry-requirements/ DCU: https://www.dcu.ie/registry/english.shtml TCD: https://www.tcd.ie/courses/postgraduate/how-to-apply/requirements/international.php |
| Funding/Stipend | EU applicants will be eligible for a full award paying fees and maintenance at standard rates. The stipend rates for 2020/21 studentships are €5,500 EU fees, stipend €18,500 per annum. |
| Contact & How to Apply | Prospective applicants should send their applications to: http://www.crt-ai.ie/apply.html. Deadline: Rolling call, the current round of applications closes on Feb 28th, 2021. |
| Additional Information | Application process. The SFI Centre for Research Training in Artificial Intelligence was established in March 2019 with funding of over €14 million from Science Foundation Ireland and an additional €3.3 million from industry and academic partners. It is Ireland's national centre for PhD-level training in AI and will train more than 120 PhDs across four cohorts, with an intake of 30 students per annum for the next four years. The centre brings together five of Ireland's seven universities and a team of almost 60 supervisors across the country. This centre is a joint initiative between University College Cork, Dublin City University, National University of Ireland Galway, Trinity College Dublin, and the University of Limerick. We offer funded PhD scholarships inclusive of fees, a monthly stipend, and a budget for travel and training. Prospective applicants should send their applications to: http://www.crt-ai.ie/apply.html Please send applications in PDF format only, the application must include the following:
The CRT aims to deliver a world class bespoke PhD training programme that will train a new generation of scholars in AI while ensuring the highest level of ethical and responsible research throughout the students training and research. This will involve five strands of study taken from topics such as Recommender System & Personalisation; Optimisation and Constraint Programming; Natural Language Processing; Machine Learning; Visual Media Processing; Ethics of Data Analytics and Fair, Accountable, Transparent AI. Each strand will be delivered by an expert and will consist of an intensive week of blended learning activities- seminars, workshops, practical tasks, group work and independent preparation. Students will develop critical skills in identifying, critiquing and applying suitable AI-based solutions both individually and in groups and learn from external experts about the latest research developments. Students will be placed with industry partners for a substantial placement experience at least once during the 4 years of the programme for a minimum duration of 3 months. All students will partake in a unique world class cohort-based PhD training programme that builds on the interdisciplinary expertise in the provision of excellent world class post graduate student training in the areas of Artificial Intelligence. Students will be mentored by the lecturers and by a team of research students and post-doctoral researchers. Female applicants are strongly encouraged to apply to our programme. Additionally, we accept applications from international students and those from underrepresented groups. This reflects each of the institutions within the CRT-AI commitment to providing a diverse and open environment for students and research/teaching staff. Start date: Studentships start from September/October 2021 Location(s): Cork, Limerick, Galway, Dublin |
| Project(s) | The IMPACT project, “Implementation of Osteoarthritis Clinical Guidelines Together” is seeking applicants for a PhD studentship commencing November 2020. IMPACT is a four-year project with research funding amounting to over €700,000 from a Health Research Board Emerging Investigator Award. IMPACT will partner with Good Life with Arthritis Denmark (GLA:D®) International Network to implement clinical guidelines for hip and knee osteoarthritis in an Irish healthcare context.
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| Faculty | Education and Health Sciences |
| Entry Requirements | Candidates must be highly motivated and have excellent research, writing, and communication skills, skills in quantitative and/or qualitative research methodologies, and some project management skills. PhD candidates will be expected to engage with practitioners and clinicians regularly, including carrying out fidelity checks and other implementation indicators. Candidates will have at least a 2.1 undergraduate degree (or equivalent) in a relevant discipline e.g. Physiotherapy, other Allied Health professional, Health Promotion, Sport Science. |
| Funding/Stipend | The studentship includes a tax-free annual stipend of €18,000 plus annual fees (EU student rate only), for 4 years. If a suitable candidate from outside the EU is recommended after interview, they will be required to supplement their fees directly or thro |
| Contact & How to Apply | Applicants should submit a detailed cover letter and a full Curriculum Vitae (including two references) to Dr. Clodagh Toomey, at clodagh.toomey@ul.ie before the closing date on October 23rd 2020 at 17.00 hours (Irish Standard Time). Informal enquiries ar |
| Additional Information | For more information: https://bit.ly/34Hwzua |
| Project(s) | Death and Burial Data: Ireland 1864-1922 (DBDIrl) You will join the DBDIrl research group, and work in collaboration with the specialists (PhD and Postdocs) in History, Digital Data Archives and Linked Data as well as other PhD students and Postdoctoral fellows in the Software System research group, working on model driven development, service oriented computing, Formal Methods, AI and data science, and Security and privacy. The co-supervisors are affiliated with Lero (www.lero.ie) and the HRI (https://www.ul.ie/hri/), various group members are affiliated with Confirm (https://confirm.ie), the ALECS EU Co-fund programme (https://alecs.lero.ie), and the CRT in AI (http://crt-ai.cs.ucc.ie). CS Background and Goals: The data management of curated digital data collections, and in particular big data, in the digital humanities is emerging as a powerful tool to make these data available to a much wider range of researchers, policy and decision makers, and general users. To make this happen, digital platforms need to be simple to use and to change, secure and efficient to use, respect the evolving data protection and legal frameworks, and have the ability to evolve and interconnect with new, heterogeneous data collections and analysis capabilities that are unknown at the conception time. For this new paradigm to enter mainstream, models need to be coupled with automatic transformations, generations, and analyses that take advantage of the formalized knowledge about the immaterial and material entities, and the individuals involved in the research. This formalized knowledge includes a variety of models together with Domain Specific Languages that use semantic types at their core. In this project, the CS team researches the underlying software and system-level challenges, and builds demonstrators of how the new thinking can disrupt the status quo but empower a better understanding. This is achieved by offering a more efficient organization and a more automated management of the many cross-dimensional issues that future digital humanities platforms - with big data, connected software and systems - will depend upon. This project is an interfaculty project between the faculties of Science & Engineering and Arts Humanities & Social Sciences |
| Faculty | Science and Engineering |
| Entry Requirements | 1. A degree (level 8 NFQ – 1st class or MSc) in Computer Science or similar disciplines 2. Excellent interpersonal, communication and organizational skills 3. Ability to work as part of an inter-disciplinary team. 4. Knowledge and experience in three or more of the following areas:
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| Funding/Stipend | EU Fees and €16000 stipend |
| Contact & How to Apply | Please review the additional information below and email address: DBDIrl@ul.ie by Friday 12pm GMT, 20 March 2020 |
| Additional Information | Please include the following information in your application: 1. A CV, 2. A cover letter describing how you meet the specification, with a description of your previous software development experience, 3. Full transcript of records of your university-level studies so far, 4. Proof of sufficient English skills (either as a native English speaker or provide an IELTS standard of 6.5 (with a minimum of 6 in all categories) or equivalent certificate), 5. Previous publications or previous significant work (thesis, final year project, or similar). Links to an online free access repository are sufficient. Please submit by Friday 12pm GMT, 20 March 2020 to the following email address: DBDIrl@ul.ie Essential pre-requisites:
Desirable competences:
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| Project(s) | MARLSITES is a joint project between University of Limerick and University College Dublin in Ireland. This project will investigate, review and evaluate forest establishment and management practices and protocols on high pH and marl sites with a view to proposing improvements that would increase forest productivity and help ensure sustainability. The study will aim to inform policy and establishment practices on these sites. The project is funded by the Department of Agriculture, Food and the Marine (DAFM) in Ireland. Two Masters projects will be funded as part of this research, as follows:
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| Faculty | Science and Engineering |
| Entry Requirements | Applications are sought from highly motivated individuals who have a good academic record in forestry, soil science, environmental science, natural resource management or closely related disciplines. |
| Funding/Stipend | Scholarship will be €24,000 per annum for two years. After a contribution to tuition fees have been deducted (€6,000 for EU students in 2019/20), the remainder of the scholarship will be paid monthly as a tax-free stipend. |
| Contact & How to Apply | Dr Ken Byrne (ken.byrne@ul.ie) The position will remain open until filled. |
| Additional Information | Applicants should submit, by email a letter outlining why they are interested in the research topic, their suitability for the position, a full curriculum vitae (including the names, addresses and emails of two referees) to: Dr Ken Byrne (ken.byrne@ul.ie). Queries about either of the two positions may be sent to Dr Byrne. |
| Project(s) | Macroalgal proteins represent interesting, but as yet, relatively unexplored sources of high quality plant-derived proteins with significant bio- and technofunctional potential. The BioDulse project, which is funded by Enterprise Ireland through the Disruptive Technologies Innovation Fund consists of a multidisciplinary team of academic and industry partners. This project is focused on extracting, characterising and ultimately developing food ingredient applications for the proteins from the red seaweed species, Palmaria palmata. A detailed understanding of the physicochemical, and both the bio- and technofunctional characteristics of P. palmata proteins and their enzymatic hydrolysates is required in order to optimise their food ingredient potential. This project aims to study the bio- and technofunctional properties of P. palmata proteins and their hydrolysates. The project will involve exposure to a range of protein science/chemistry, technofunctional and in vitro bioactivity assessment techniques during the extraction and characterisation of macroalgal proteins and their hydrolysates.The increasing consumer demand and a rapidly growing global population highlights the need to find sustainable alternative food protein sources. Macroalgae, or seaweed, has been consumed throughout the world for centuries. |
| Faculty | Science and Engineering |
| Entry Requirements | Minimum 2.1 hons degree in Food Science, Food Chemistry, Biotechnology, Bioscience, Biochemistry or closely related discipline |
| Funding/Stipend | €21,690 per annum (value includes postgraduate fees) |
| Contact & How to Apply | Prof. Dick. FitzGerald, Biological Sciences Department, University of Limerick, Limerick, Ireland. Tel: 00353 061 202598: E-mail:dick.fitzgerald@ul.ie dick.fitzgerald@ul.ie |
| Additional Information | Applicants are invited to submit a cover letter, recent CV and two academic references to Prof. FitzGerald |
| Project(s) | The successful candidate will support a project funded by the Lifes2good Foundation in conjunction with Connacht Rugby. Data on youth rugby players in the province of Connacht suggest that dropout is particularly severe between the ages of 16 and 20 years. Continued participation in sport at this age is viewed as an important avenue to promote physical, mental and social health. Decisions about sport participation arise from the complex interaction of a broad range of factors. Although some of these factors are likely to underpin continued participation irrespective of context (e.g., enjoyment; quality relationships), context-specific investigations are required to identify the specific barriers to and sources of support for continued participation. The project will examine ways in which Connacht Rugby could support the underage player pathway to better facilitate the playing experience, reduce drop out and ultimately see more players continuing to adulthood as participants in rugby at all levels. |
| Faculty | Education and Health Sciences |
| Entry Requirements | Essential Criteria •Bachelor’s degree in a health science field (2.1 award or higher). •Evidence of excellent communication skills. •Evidence of excellent organisational skills. •Evidence of excellent IT skills. •Car owner and full driving license. Desirable Criteria •Evidence of research report writing. •Evidence of experience using qualitative research methods, particularly in relation to focus groups. •Coaching experience within a youth sport context. •Demonstrated experience of working effectively in a research team as well as independently. |
| Funding/Stipend | |
| Contact & How to Apply | For further information please contact Dr Philip Kearney, email philip.kearney@ul.ie |
| Additional Information | Additional information on the project, including a detailed description, the terms of the award, and guidance on how to apply, is available here |
| Project(s) | Energy systems around the world are currently undergoing two simultaneous and radical transformations; the electrification of transport and the decarbonisation of the electricity grids. Likewise, there are highly ambitious aspirations at a policy level to transition from a linear economy to a circular economy and in particular in the area of critical raw materials where recycling rates are very low and for which Europe is dependent on largely single sources which are considered to be a supply risk. This project is at the nexus of these challenges. It will undertake a detailed scientific, technical and economic analysis into how the batteries of end-of-life electric vehicles can be repurposed as stationary batteries to support the greater integration of renewable electricity in electric grids. This incorporates forecasting the availability of storage capacity based on quantitative projections of electric vehicles reaching end of life, testing of business models for their use in grid applications, a physical model as to how the batteries will perform over the necessary extended lifecycles in these business models, and recommendations on ELV treatment standards to facilitate the opportunity. The project will deliver an evidential basis for policy makers to support their planning for the coming energy, transport and circular economy transitions that are necessary in the pursuit of EU targets and the UN Sustainable Development Goals. |
| Faculty | Science and Engineering |
| Entry Requirements | Candidate Requirements Essential Attributes: A Bachelors degree in Electronic/Electrical/Computer Engineering or equivalent. A strong interest/experience in data analytics. Desirable Attributes: A Masters degree in Electronic/Electrical/Computer Engineering or equivalent. Publication in conference and/or peer-reviewed journal. Experience in analysis of electric grids. |
| Funding/Stipend | Stipend of €16,000 tax free per annum, EU tuition fees covered. Non-EU students may have to pay balance of full fees. |
| Contact & How to Apply | For further information please contact Colin.Fitzpatrick@ul.ie. To apply please send a cv and application letter to Colin.Fitzpatrick@ul.ie |
| Additional Information |
| Project(s) | The contribution of the oncogenic Epstein-Barr virus to the pathogenesis of B cell malignancies. |
| Faculty | Education and Health Sciences |
| Entry Requirements | An appropriate Masters Degree or Primary Degree Level (first class hons or 2.1 hons) in a relevant discipline. |
| Funding/Stipend | Stipend of €16,000 tax-free per annum, EU tuition fees covered. Non-EU students may have to pay balance of full fees. |
| Contact & How to Apply | A CV, University transcripts, 2 academic references and a letter of application indicating why you think your skills and experience meet the requirement for the project. For Further Details, please contact via email Professor Paul Murray paul.murray@ul.i |
| Additional Information | The majority of B cell malignancies arise within the germinal centre, a stage of B cell differentiation associated with significant genetic instability. The Epstein-Barr virus (EBV) is a human herpesvirus that can colonise germinal centre B cells as part of its natural life cycle in the asymptomatic host. However, EBV is associated with the development of germinal centre derived B cell malignancies. This project seeks to unravel the contribution of EBV and its latent genes to the pathogenesis of germinal centre derived tumours using new models of disease to understand how EBV co-operates with other cellular mutations. There will be opportunities for study in other laboratories abroad as part of this studentship, including research groups at the University of Birmingham and the University of Cambridge. For further reading see: Young LS, Yap LF Murray PG. Nat Rev Cancer 2016 12: 789-802 Shannon-Lowe et al Philos Trans R Soc Lond B Biol Sci 2017 372:1732 |
| Project(s) | The contribution of CAMK1D to the pathogenesis of Hodgkin lymphoma |
| Faculty | Education and Health Sciences |
| Entry Requirements | An appropriate Masters Degree or Primary Degree Level (first class hons or 2.1 hons) in a relevant discipline |
| Funding/Stipend | Stipend of €16,000 tax-free per annum, EU tuition fees covered. Non-EU students may have to pay balance of full fees. |
| Contact & How to Apply | A CV, University transcripts, 2 academic references and a letter of application indicating why you think your skills and experience meet the requirement for the project. For Further Details, please contact via email Professor Paul Murray paul.murray@ul.ie |
| Additional Information | New approaches to the treatment of Hodgkin lymphoma (HL) are needed to increase survival for patients with resistant or relapsed disease and to reduce the acute and long-term side effects of current therapies that adversely impact on the health and well-being of survivors. In this project, we will measure the expression and activation of CaMK1D in relation to disease outcomes in HL patients. We will also explore the impact of CaMK1D inhibition on the phenotype of HL cells, including aberrant cellular signalling, in vitro and evaluate the potential therapeutic effects of CaMK1D inhibitors alone and in combination with standard chemo-therapeutics in xenograft models. The student will receive a broad range of training and there will be opportunities to spend part of the studentship working in the University of Birmingham Cancer Research Centre. |
| Project(s) | Full details available http://www.ul.ie/psychology/phd-studentships |
| Faculty | Education and Health Sciences |
| Entry Requirements | |
| Funding/Stipend | |
| Contact & How to Apply | Further Details http://www.ul.ie/psychology/phd-studentships |
| Additional Information |