Title: Towards the development of a next generation, biomimetic embryo culture and diagnostics system for assisted human reproduction (embryoFlow)
One in six couples worldwide have problems conceiving and many of these will undergo fertility treatment. Within fertility clinics two out of three cycles fail due in-part to inadequate in vitro embryo culture conditions, whereby embryos are cultured in static droplets (in their own waste products) under mineral oil (to prevent evaporation) for five days. This contrasts to a delicate changing milieu in vivo whereby, the developing embryo moves down the fallopian tube and into the uterus in the first few days after fertilisation. Therefore, the aim of this innovative and exciting project is to apply design thinking to design, develop and test a state-of-the-art in vitro biomimicry embryo culture prototype system to maximise the chance for a successful treatment outcome for couples undergoing fertility treatment.
The embryoFlow system will be built on a microfluidics platform (already developed for sperm selection) which will allow embryos to be cultured individually in microdroplets with the media changed regularly without disturbing the embryo. This embryo secretome in the spent culture media can be used in diagnostics to determine the molecular signature of the embryo. When combined with time-lapse imaging this will inform the embryologist and couple on which embryo will give the best chance of a successful pregnancy.
- Minimum of a BSc (Hons level 8) in a Design Engineering or related discipline
- Experience of design research methodology and application, or similar
- Qualitative research methodology experience, including data collection and analysis
- Experience with CAD software and prototyping processes such as CNC machining, 3D printing and hand-finishing
- Enthusiastic individual with motivation to work on own and as part of a multidisciplinary team
- Full clean driving licence and own car an advantage
Please send a CV, a cover letter, and a copy of university transcripts to email@example.com by 22 August 2022. Application Submission: Please note that only short-listed candidates will be informed regarding their application status.
This is an exciting opportunity to join a multidisciplinary team at the University of Limerick.
- Dr Eoin White is a Lecturer in Design for Health & Wellbeing within the School of Design and his research focuses on medical device development, design validation, human factors and regulatory considerations.
- Professor Sean Fair is a Principal Investigator within the Biomaterials Research Cluster, Bernal Institute at the University of Limerick. He leads a large well-funded internationally focused research team in Reproductive Biology which is focused on using in vitro and in vivo animal models to understand how gametes interact with the female reproductive tract. The successful candidate will be primarily based in the School of Design but will work with Professor Fair’s research group as well as other academic and industry partners.
Applications are invited for a four-year PhD Studentship in early modern history. The successful applicant will join the ‘Malcontents: Order and Disorder in the Early Modern World of Learning’ project which is led by Dr Richard Kirwan of the Department of History and the Centre for Early Modern Studies, University of Limerick. The project will be funded by the Irish Research Council.
The Malcontents project aims to explore outsider experiences in the early modern world of learning with a focus on the universities of the Holy Roman Empire and the Low Countries. The project will uncover the processes that led to the identification of social and intellectual deviance and the marginalisation of malcontents in universities. In doing so, the project will establish how the treatment of deviance facilitated the substantiation of order in the early modern university and beyond.
As part of the Malcontents project, the PhD Studentship awardee will carry out research on aspects of student deviance in the early modern university with a focus on the Holy Roman Empire. This will form the basis of a PhD dissertation.
Applications are sought from candidates who hold or are in the process of completing a master’s degree in history or cognate discipline. Knowledge of German is essential. Candidates with a first-class honours undergraduate degree combining history and German may also be considered in cases where a dissertation on early modern German history has been completed.
Dr Richard Kirwan firstname.lastname@example.org
Candidates should apply by sending by email a cover letter, CV, transcripts of university degrees, two letters of recommendation from academic referees, and a writing sample of 2,000 words to the P.I., Dr Richard Kirwan (email@example.com), by 22nd July 2022. The successful candidate will be required to apply formally to be admitted as a PhD student by the University of Limerick. To this end, applicants who do not have English as their first language should include the following with their application: an English translation of qualification(s)/transcripts and an English language competency certificate.
Applications are invited for one of three funded four-year PhD Studentships in Youth Justice. The successful applicant will join the North South Research Programme project ‘Stable Lives Safer Streets Hub’ (SLSSHub) and the Research into Policy Programmes and Practice Project (REPPP) in the School of Law, University of Limerick (UL).
SLSSHub is a collaborative project between UL, Queens University Belfast, and the Center for Effective Services. The hub aims to develop a multi-disciplinary cross-border policy-led research hub of excellence in Youth Justice. As part of the SLSSHub, the PhD Studentship awardee will work with the team lead on one of two engaged research work programmes
- Develop a standardise measurement tool for young people enrolled on targeted youth justice prevention and intervention programmes.
- Implementation of an element of the National Youth Justice Strategy (2021-2027) and the NI Strategic Framework for Youth Justice (2022-2027) (2 positions)
Applications are sought from candidates who hold or are in the process of completing an undergraduate or master’s degree in a social science, applied maths, computer science or cognate discipline with a 2.1 Honours degree or higher.
Candidates should have good methodology skills, be highly motivated, with the ability to work on their own initiative and as part of a multi-disciplinary team. Candidates should have strong inter-personal skills with an ability to engage with external stakeholders.
Dr Catherine Naughton, PI SLSSHub, REPPP, School of Law, University of Limerick Email: Catherine.Naughton@hiendhawaii.com
Prospective applicants should email to Catherine.Naughton@hiendhawaii.com by 17th August 2022.
- 2-page Curriculum Vitae
- Short cover letter indicating your motivation and interest in one of the two projects (maximum one page)
- A writing sample of 2,000 words
- 2 Referees
- Please include SLSShub_PhD and your name in the subject line.
Applications should be submitted in PDF format only. The PhD Studentship will commence in September 2022.
The successful candidate will be required to apply formally to be admitted as a PhD student by the University of Limerick.
Enquiries can be directed to Dr Catherine Naughton
Each PhD student will receive a stipend of €18,500 per annum for four years. The studentship also covers EU tuition fees for four years (renewed annually). Non-EU applicant welcome but will need to self-finance the balance of the non-EU fees. A travel allowance is included to facilitate travel, training and conference attendance, and a mobility allowance if the awardee chooses to relocate to Queens University Belfast for 12 months.
Mathematical modelling of chemical transport in a porous medium with evolving microstructure
This project is a full-time 4-year structured PhD project based in the Mathematics Applications Consortium for Science and Industry (MACSI) in the University of Limerick. The funding includes a tax-free stipend (with fees paid) along with expenses for computing equipment, conference travel and materials.
The research topic is mathematical analysis of porous systems with an evolving microstructure. Dissolving tablets, brewing coffee and battery operation all require transport of chemicals through liquid-filled porous structures. Transport across these systems is strongly dependent on microstructural properties (e.g., porosity, tortuosity, permeability), and often these properties change during interactions between the solid, liquid, and dissolved chemicals.
In this project, perturbation methods (also known as asymptotic analysis) will be developed for accurately modelling macroscale dynamics in structured porous media. The candidate will learn to use mathematical homogenization to systematically account for an evolving microstructure and link microscale phenomena to macroscale behaviour. The derived models will be deterministic in nature and will be analysed and solved using a combination of dimensional analysis, asymptotic methods, and numerical techniques. The methodology will be applied to extend models of drug release from tablets, gels, and stents to include biodegradation, with the goal of facilitating the understanding and control of such systems. Wider applications include coffee brewing, battery technology and contaminant transport.
Applicants should have, or expect to attain (prior to project start), at least a 2.1 honours degree or equivalent in the areas of mathematics, applied mathematics, physics or engineering.
Applicants with other relevant qualifications or experience who can show evidence of proficiency in high-level mathematics may also apply.
Applicants for whom English is a second language will be required to demonstrate their competence in English language in line with University of Limerick requirements.
Dr. Kevin Moroney, Lecturer in Industrial and Applied Mathematics
MACSI, Department of Mathematics and Statistics
University of Limerick. Email: firstname.lastname@example.org
Applications should be submitted in PDF format only.
The research will be conducted within the Mathematics Applications Consortium for Science and Industry (MACSI) research centre, Ireland’s foremost applied and industrial mathematics and statistics group.
The funding is conditional on the successful applicant being registered before 31st December 2022.
Prospective applicants should email their applications to Dr. Kevin Moroney (email@example.com) before 30th June 2022. Applications must include the following:
- 2-page Curriculum Vitae including at a minimum the applicants name, education institution, qualification stating overall grade/percentage (predicted grades are acceptable for those still studying)
- Short cover letter/statement of purpose (maximum 2-pages) indicating their motivation and interest in the position.
- Please include “PhD Application” followed by your name in the subject line.
- 2 referees
Applications should be submitted in PDF format only.
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.
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.
Dr Tom Newe, email: firstname.lastname@example.org
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-Profile, Linkedin) (UL) and Dr Mubashir Rehmani (Linkedin) (MTU@Cork).
Please submit your CV to Thomas.email@example.com 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.
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.
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
The successful candidate will work within the Data-driven Intelligent Computational Engineering Group in UL, under the supervision of Dr. Ciarán Eising (link, link) 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 firstname.lastname@example.org, 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 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).
Dr. Tom Comyns email@example.com or Dr. Ian Kenny firstname.lastname@example.org 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.
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.
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.
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
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.
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.
For more information: http://bit.ly/34Hwzua