Project(s)

Over the past number of decades the electric grid has been modernized, becoming more decarbonized, distributed and digitalized. As a consequence modern day electric grid systems have evolved to become smart grids allowing: two way flow of electricity and data enabling applications such as smart metering; deregulation of the energy market introducing new players in the generation and supply of electricity; and decentralization (distributed generation of electricity) and corresponding emergence of ”prosumers” who can both produce and consume electricity; and microgrids providing small, local distribution systems that can be connected to the main grid or operated independently.

Entry Requirements

The ideal candidate will have a Bachelor’s (BE/BSc) or a Master’s (ME/MSc) Degree in Electronic Engineering, Computer Engineering, Computer Science, Electrical Engineering, or a related numerate/STEM discipline.

Good knowledge of/Interest in SDN would be of benefit. 

Funding/Stipend
EU applicants will be eligible for a full award paying fees and maintenance at standard rates. The stipend rates for studentships are €5,500 EU fees, stipend €18,500 per annum. Travel and equipment costs also included.
Contact & How to Apply

Dr Tom Newe, email: thomas.newe@ul.ie 

Additional Information

This project is co-funded between the SFI Advance CRT and the SFI Confirm Research Centre. The supervision team will consist of: Prof Donna O’Shea (Linkedin) (MTU@Cork), Dr Tom Newe (UL-ProfileLinkedin) (UL) and Dr Mubashir Rehmani (Linkedin) (MTU@Cork).

Please submit your CV to Thomas.newe@ul.ie including details of at least two referees. Shortlisted applicants may be invited to interview. On receiving an offer, the successful applicant will be required to submit supporting documentation (e.g., Copies of degree certificates and English language competency where required).

The successful student can be based in either Limerick or Cork but will need to spend time in both campuses, MTU and UL over the four years for different aspects of the work.

Project(s)

We are accepting applications for a new PhD Scholarship based at the University of Limerick (UL)

The project BEMAP, examines Mercury-Added Products (MAPs) in the Built Environment (BE).  MAPs such as fluorescent lighting are a significant environmental hazard if not managed appropriately. Many MAPs are also e-waste or WEEE (Waste Electrical and Electronic Equipment), the maltreatment of WEEE poses contamination risks to the environment, missed employment opportunities in the disassembly and treatment sector and loss of precious materials to the circular economy. The removal of all anthropogenic sources of mercury output to the environment is a key objective of the Minamata Convention. Development and refinement of inventory tools and models to track mercury emissions is key to assisting mercury capture. 

This research seeks to identify current MAP stocks in the BE using data harvesting and modelling techniques, thereby contributing to inventory tools and models of mercury emissions from key anthropogenic sources.

Entry Requirements
  • Applicants should hold a 2.1 higher honours undergraduate degree or Masters in Science/Engineering (Environmental, Mechanical, Electronic, or related field).
  • Strong interest in environmental aspects of e-waste, hazardous materials management, and circular economy; prior research experience in material flow analysis would be advantageous.
  • Candidates are required to provide evidence of English language ability as per local University guidelines.
  • Excellent communication skills and experience in working in multidisciplinary teams.

Strong motivation to tackle challenging research problems

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

Dr Yvonne Ryan Yvonne.Ryan@ul.ie 

Additional Information

The successful candidate will join the Electronic and Computer Engineering Department, at the University of Limerick, working under the supervision of Dr Yvonne Ryan (UL Profile) (LinkedIn) (Research Gate) and Prof. Colin Fitzpatrick (UL Profile)To apply,

please submit your CV to Yvonne.Ryan@ul.ie including details of at least two referees. Shortlisted applicants may be invited to interview.

On receiving an offer, the successful applicant will be required to submit supporting documentation (e.g., Copies of degree certificates and English language competency where required).

Project(s)

The Data-driven Intelligent Computational Engineering (D2ICE) Group at the UL Dept of Electronic and Computer Engineering, in collaboration with Provizio and Lero, the SFI Research Centre for Software, are seeking a PhD candidate to work on an exciting project in the application of machine learning in radar and visual sensing for the prevention of road accidents. Given the wealth of information that is potentially available in radar-fusion sensing, there is a strong potential for machine learning algorithms to provide recognition, tracking, and prediction tasks for driver assistance and automated driving systems. For example, the position and trajectory of a pedestrian, vehicle or cyclist can be tracked and predicted, enabling a safer reaction of the host vehicle.

The project will be in collaboration with Provizio, who are headquartered in Limerick City. The Provizio team is made up of experts in robotics, artificial intelligence, computer vision and radar sensor development and are building an augmented, ‘guardian angel’ platform that could prevent road accidents. The candidate will work on AI solutions for automotive accident prevention using Provizio 5D radars with AI on-the-edge.

 

 

Entry Requirements

The ideal candidate will have a Bachelor’s (BE/BSc) or a Master’s (ME/MSc) Degree in Electronic Engineering, Computer Engineering, Computer Science, Computational Mathematics, or a related numerate discipline.

Skills and Competencies:

The successful candidate will…

  • Be passionate about artificial intelligence and machine learning
  • Be enthused by the opportunity to work closely with industry collaborators
  • Have strong computational skills (e.g., Python, MATLAB, C/C++, etc.)
  • Have experience with machine learning tools (e.g., Scikit-learn, Tensorflow, PyTorch, etc.)
  • Be comfortable with managing and curating large datasets
  • Be self-motivated, output driven, and have good communication and presentation skills

The following attributes are desirable, but not required:

  • Knowledge of radar systems or processing of radar data
  • Industrial experience
  • Experience in the use of neural networks, particularly CNNs
  • Track record in publication of research
Funding/Stipend
Stipend €18,500 normally tax free per annum, and EU tuition fees covered for a period of 4 years. Non-EU students may have to pay balance of full fees.
Contact & How to Apply
To apply, please submit your CV to ciaran.eising@ul.ie, including details of at least two referees. Shortlisted applicants may be invited to interview.
Additional Information

The successful candidate will work within the Data-driven Intelligent Computational Engineering Group in UL, under the supervision of Dr. Ciarán Eising (linklink) and Dr. Pepijn Van De Ven (link). This is a dynamic group of like-minded researchers investigating many applications of machine learning and computer vision, in areas such as automotive, robotics, medical, health and municipal, among others. The post is available on the 1st of January 2022 (or as soon as possible after that date).

To apply, please submit your CV to ciaran.eising@ul.ie, including details of at least two referees. Shortlisted applicants may be invited to interview. On receiving an offer, the successful applicant will be required to submit supporting documentation (e.g., Copies of degree certificates and English language competency where required).

Project(s)

The research will involve working with schools and medical teams to survey and measure the incidence, nature, severity and prevention of injury within the youth game, and conduct on-going monitoring of injury trends. The research will implement injury prevention interventions at the school level based on findings and determine the impact of these interventions on injury patterns within the schools game. 

The University of Limerick (UL) with close to 16,500 students, including 2,000 international students and 1,300 staff is an energetic and enterprising institution with a proud record of innovation and excellence in education, research and scholarship. The dynamic, entrepreneurial and pioneering values which drive UL’s mission and strategy ensures that we capitalise on local, national and international engagement and connectivity. The reference to UL as ‘Ireland’s Sporting Campus’ is very much as a consequence of the University’s strategy to create a world class sporting infrastructure. The building infrastructure is complimented by leading research facilities and staff from all aspects of sport and exercise sciences, and clinicians from UL’s Health Research Institute (HRI).

Entry Requirements
• Students will normally need to hold at least a 2:1 degree (or equivalent) in Sports Science, Physiotherapy or a related discipline. A relevant Master’s degree will be an advantage, as will experience in completion of a major research project.  • Proven research experience and involvement in the Rugby industry will be an advantage. • The PhD candidate will be required to travel independently to Rugby schools both locally and country-wide. • The candidate must possess excellent written, verbal and presentation skills for both specialist and non-specialist audiences; excellent interpersonal skills; ability and experience in collaborating effectively in teams; familiarity with advanced statistics; an ability to work independently and with initiative at a high level of self-motivation; high level attentiveness to detail. • This position is subject to Garda vetting and foreign police clearance.
Funding/Stipend
Stipend of euro €18,000 per annum plus tuition fees at the EU rate. International (non-EU) students may apply but will need to self-finance the balance of the non-EU fees. Funded by the Irish Rugby Football Union.
Contact & How to Apply
To apply, please send applications directly to the following e-mail address: rugby.surveillance@ul.ie The application must comprise two documents: 1. One-page cover letter briefly outlining applicant suitability and motivation for the PhD research topic,
Additional Information
For informal enquiries about the project, please contact 
Dr. Tom Comyns tom.comyns@ul.ie  or Dr. Ian Kenny ian.kenny@ul.ie    Location: University of Limerick, Ireland Deadline: 17.00 Irish time (GMT) 19th of November 2021 Interview date: Tuesday 7th of December Start date: January 2022 Duration: Four years full-time (structured PhD) Description: Applications are invited for a PhD studentship funded by the Irish Rugby Football Union to start in January 2022. The project will be based in the Department of Physical Education and Sport Sciences at the University of Limerick. The successful candidate will be supervised by Dr. Tom Comyns, Dr. Ian Kenny and Dr. Kieran O’Sullivan from the University of Limerick, in collaboration with the Irish Rugby Football Union Medical Department. The aims of the PhD will be: • Support the research programme team to maintain implementation of their injury surveillance system (IRISweb) for the schools’ game in Ireland which allows for the collection, tracking and trend analysis of injury patterns (incidence, nature and severity), in order to identify possible injury casual factors and prevention strategies. • Expand the injury surveillance system (IRISweb) within the school cohort in Ireland. • To enhance the health and welfare of Rugby Union players across the schools game in Ireland by providing information on injury patterns that can impact on IRFU policy regarding injury prevention measures and by researching the impact of injury prevention strategies on the injury profile of Irish school players. 
Project(s)

Funded PhD Project in Molecular Modelling at the Bernal Institute at University of Limerick. 

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  
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. 

 

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/

UL:       https://www.ul.ie/international/non-eu-exchange/incoming-non-eu-exchange/english-language-requirements

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:

  • Curriculum Vitae.
  • Cover letter explaining interest in research, referring explicitly to one or more of the areas listed above. (maximum 3 pages);
  • Career Statement with justification as to why you want to complete a PhD (maximum 3 pages);
  • Proof of degree and transcripts of results (single PDF); Any additional supporting document you would like to have considered (if applicable, single PDF).

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.
 
The role of this PhD will be to evaluate if online delivery of a group exercise and education programme for hip and knee osteoarthritis is effective in reducing self-reported symptoms and pain and improving quality of life at 3- and 12-months follow-up, compared with conventional face-to-face programme delivery. There will also be an opportunity to compare findings within the GLA:D international network.

 

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

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: 
  • Ontologies, linked data or similar domain description techniques
  • Data science/analytics, information system design and development
  • Development in Java and other programming languages/paradigms
  • Familiarity and experience of Model Driven Design and Development concepts and tools 
  • Familiarity with agile software development, agile project management, DevOps
  • User interface design (HCI, UX), web development (Angular JS or equivalent) 
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:

  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:
  • Ontologies, linked data or similar domain description techniques
  • Data science/analytics, information system design and development
  • Development in Java and other programming languages/paradigms
  • Familiarity and experience of Model Driven Design and Development concepts and tools
  • Familiarity with agile software development, agile project management, DevOps
  • User interface design (HCI, UX), web development (Angular JS or equivalent)

Desirable competences:

  • Demonstrated experience and understanding of digital humanities requirements.
  • Evidence of report writing skills
  • Experience of co-writing and co-researching articles. 
  • Publications/and conference papers in HCI, software modeling or programming, or Digital Humanities
     
  • Please submit by Friday 12pm GMT, 20 March 2020 to the following email address: DBDIrl@ul.ie
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:
MSc 1. Soil properties influencing forest growth and development on high pH and marl sites. The student will investigate soil properties at a range of study sites on high pH and marl sites. This MSc will be based at the University of Limerick and will be supervised by Dr Ken Byrne (University of Limerick) and Dr Thomas Cummins (University College Dublin).

 

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.