Vacancies
Welcome to the School of Computer Science and Statistics! We are a thriving multidisciplinary school encompassing five disciplines with over 130 academic, teaching, research and support staff. The school hosts two cutting-edge SFI Research Centres and is located across eight locations on campus. As an integral part of the E3 initiative, we collaborate closely with the Schools of Engineering and Natural Sciences to drive ground-breaking research and education.
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Our commitment to excellence is evidenced by being the leading university in Ireland in Computer Science and ranked in the Top 100 globally.
Whether you are starting your academic career or seeking to advance your expertise, the School of Computer Science and Statistics is the perfect place to thrive and innovate.
PhD Opportunities
A number of fully funded PhD scholarships are available in the area of Predictive Maintenance & Early Warning Systems. The Studentships will provide a tax-free bursary of €25,000 per annum for 4 years together with fee payment. Applications ought to have a 2.1 or 1 Degree in Computer Science or cognate discipline and/or an M.Sc in Computer Science/cognate discipline. Applications will be received until the positions are filled.
Prospective candidates would be expected to have an interest in several of the following areas: Artificial Intelligence, Multi-Agent Systems, Machine Learning, Data Analytics, IoT systems & Ubiquitous Sensing. Interested parties should send a detailed academic Curriculum Vitae together with a letter of application indicating their interest in research, Trinity College SCSS and CKDelta programme, to Professor Gregory O’Hare Gregory.OHare@tcd.ie with a subject heading 'AI PhD Application'.
Post Summary
Novel optical access and metro networks are essential to support fast growing capacity requirement, driven by future applications and services for 6G and beyond. Networks are also evolving to support a large variety of signals across larger access and metro network areas. For these novel scenarios, flexibility becomes an essential feature, driven by the development of flexible components and open networks.
Development of Digital Twins, capable of building dynamic models from information gathered form live networks become essential to manage network requests, while maintaining high availability and optimal resource utilization.
One PhD studentship is available for work in the area of Digital Twins for optical networks, making use of intelligent AI-driven control planes. The work will involve: i) (i) development of network probing algorithms for OSNR/GSNR measurement automation; (ii) development of adaptive ML and critical component analysis, and (iii) development of Automation of ML model and data selection.
The applicants should have knowledge of machine learning and optical networks and willing to engage in testbed-oriented research. The work will be carried out in the new OpenIreland research infrastructure, a large-scale testbed for experimentation in open optical, wireless and cloud technologies.
The position will be based in the School of Computer Science and Statistics at Trinity College Dublin, Ireland and will be funded under the Science Foundation Ireland Investigators award project. The researcher will have the opportunity to build their research portfolio within a range of projects within Prof. Ruffini’s Research group. The researcher will also be part of the School
of Computer Science and Statistics in TCD. The position will be under the direction of Prof. Marco Ruffini
Closing Date: 12 Noon (Irish Standard Time), [30 May 2025]
Project title: Developing and Evaluating Interpretable Approaches for Human-Centered Machine Learning.
Project supervisor: Dr. Eoin Delaney (Trinity College Dublin).
Project locations: Discipline of Statistics and Information Systems, School of Computer Science and Statistics, Trinity College Dublin.
Application deadline: 12th May 2025
Start date: Anticipated start date is September 2025
PhD structure: The funding for the project includes a tax-free stipend of €25,000 per annum. In addition to stipend, EU fees will be covered for four years.
PhD topic: Approaches in interpretable machine learning offer promise in understanding the predictions of opaque models that are widely deployed in high-stakes decision making scenarios. Of particular interest to this project are example-based
explanation methods that use individual data points or examples to provide insights into the decision making process of complicated models. This family of explanations has both rich statistical and psychological grounding and the project will look to investigate the utility and the robustness of different explanation strategies.
A large focus of this project will be on leveraging novel and interpretable approaches in applied domains such as algorithmic fairness and time series prediction for sustainable practices. As explanations are ultimately for end users, it is crucial to consider how they can impact trust in automated decision-making, creating a need for human-centred and psychologically informed methods that could encourage responsible behaviours. Designing such approaches for opaque generative models, such as Large Language Models (LLMs), is critical and is also of growing interest to industry.
Conditions of the Award
The conditions are listed on the TCD website: https://www.tcd.ie/graduatestudies/awards/trda-school-based/
- Open only to new entrants to the full-time research doctorate register (EU and non EU).
- The holders must engage in full-time research and must register for a research doctorate degree at Trinity College, the University of Dublin.
- Continuation on the research register is dependent on evidence of satisfactory annual progress and successful completion of the confirmation process at 18 months after first registration.
- Both the doctorate researcher and supervisor will agree to participate in the pilot rollout of Trinity’s Supervisor: Research Student Agreement.
- Postgraduate Research Doctorate Awards cannot continue beyond a fourth year on the full-time research doctorate register and cannot be split across doctorate researchers.
- Decision on allocation of the award rests with the School.
Stipend details
The award includes a stipend of €25,000 p.a. and fees write-down (EU or non-EU) for the four years (full-time) of a Structured PhD programme / research doctorate.
Application criteria
The award is expected to be very competitive, therefore the minimum requirement is a 2.1 honors (or equivalent) undergraduate degree and a distinction (or equivalent) MSc degree. Candidates without an MSc or a lower grade degree will not be considered.
Application process
All application materials should be submitted by the prospective supervisor, no later than Friday May 30th, with the subject line “School-based Trinity Doctoral Research Award” to SCSS DTLP at gavin.doherty@tcd.ie, HoS at headscss@tcd.ie and Natasha Blanchfield at Natasha.Blanchfield@tcd.ie.
Late or incomplete applications will not be considered.
Applications should contain the following in pdf format:
Provided by the candidate:
2. CV
4. Proof of English language qualifications, if required (according to English language requirements on https://www.tcd.ie/study/apply/admission-requirements/postgraduate/index.php)
5. 2 academic reference letters
6. 2 page research proposal, to also address how does the proposed research fit within SCSS research themes and proposed supervisor’s interests
Project title: Explaining and Mitigating Bias in Advice from Large Language Models.
Project supervisor: Dr. Eoin Delaney (Trinity College Dublin) and Prof. Mark Keane (University College Dublin).
Project locations: School of Computer Science and Statistics, Trinity College Dublin.
Application deadline: 02 June 2025. Applications will be reviewed on a rolling-basis and early application is strongly recommended.
Start date: September 2025.
PhD structure: The funding for the project includes a tax-free stipend of €25,000 per annum. In addition to stipend, fees will be covered for four years and there is a budget for equipment and conference travel. This project is supported by the Central Bank of
Ireland and the Insight Centre for Data Analytics which is funded by Research Ireland.
PhD topic: This project aims to address how language models can nudge people towards irresponsible behavior by amplifying existing cognitive biases. We aim to: (1) develop novel human-centered explanation techniques that help people to critically
evaluate generative AI models with a focus on financial advice; (2) provide empirical evidence on how advice from Large Language Models (LLMs) can be overconfident and biased; and (3) create practical guidelines for responsible AI system design. By
combining insights from cognitive psychology with explainable AI (XAI) techniques, our work directly supports the Central Bank's regulatory objectives under the EU AI Act by addressing systems that could deploy subliminal, manipulative, or deceptive techniques, impairing informed financial decision-making. The resulting frameworks from this project will equip practitioners with evidence-based approaches for evaluating and regulating AI advisory systems while protecting people as these technologies become increasingly prevalent.
Research Opportunities
Post Summary
The Research Assistant will join an interdisciplinary team working on the use of locative games for cultural heritage sites. The project, entitled LoGaCulture, is funded through Horizon Europe and has partners from four European countries. The TCD team is led by Prof. Mads Haahr and is conducting research, design and development in locative games and interactive digital narrative. The Research Assistant is expected to participate actively in the project with specific focus on user study.
Closing: 12 Noon (GMT), 29th May 2025
Post Summary
The Complex Software Lab at Trinity College Dublin invites applications for a Postdoctoral Researcher position in Software Testing and Artificial Intelligence. This post is part of a collaborative project between Trinity College Dublin, Lero (the SFI Research Centre for Software), and software company ServiceNow, focused on the development of novel AI-enhanced methods for software testing and quality assurance in enterprise systems.
The researcher will work on designing and evaluating techniques for testing AI-integrated software systems, including model robustness, test automation, and the interaction between traditional software testing and Machine Learning components. This research will have real-world impact through close collaboration with industry partner and offers the opportunity to contribute to cutting-edge advancements in trustworthy AI and Software Engineering.
Closing Date: 12 Noon (GMT), 29th May 2025
We are seeking a highly motivated candidate for a fully funded postdoctoral researcher
position to work in 3D computer graphics and 3D computer vision.
The successful candidate will join the 3D Graphics and Vision research group led by
Prof. Binh-Son Hua at the School of Computer Science and Statistics, Trinity College
Dublin, Ireland to work on topics related to generative AI in the 3D domain.
The School of Computer Science and Statistics at Trinity College Dublin is a collegiate,
friendly, and research-intensive centre for academic study and research excellence. The
School has been ranked #1 in Ireland, top 25 in Europe, and top 100 Worldwide (QS
Subject Rankings 2018, 2019, 2020, 2021).
The postdoctoral researcher is expected to conduct fundamental research and publish
in top-tier computer vision and computer graphics conferences (CVPR, ECCV, ICCV,
SIGGRAPH) and journals (TPAMI, IJCV). Other responsibilities include supporting
graduate or undergraduate students with technical guidance and engagement in other
research activities such as paper reviews, reading group, workshop organization, etc.
The start date of the position will be as soon as possible. Contract duration is 1 year with
the option of renewing for a second year.
The successful candidate will require the following skills and knowledge:
• PhD in Computer Science or related fields;
• Strong tracked records in 3D computer graphics, 3D computer vision;
• Hands-on experience in training deep models and generative models is required;
• Hands-on experience and relevant skills in computer graphics and computer
vision application development such as OpenGL, OpenCV, CUDA, Blender is
desirable;
• Strong programming skills in C++, Python. Capability in implementing systems
from research papers and open-source software.
• Additional background in math, statistics, or physics is an advantage.
Full Description: Postdoctoral Researcher
We are seeking a highly motivated candidate for a research assistant position to work in
3D computer graphics and 3D computer vision.
The successful candidate will join the 3D Graphics and Vision research group led by Prof. Binh-Son Hua at the School of Computer Science and Statistics, Trinity College Dublin, Ireland to work on topics related to generative AI in the 3D domain.
The School of Computer Science and Statistics at Trinity College Dublin is a collegiate, friendly, and research intensive centre for academic study and research excellence. The School has been ranked #1 in Ireland, top 25 in Europe, and top 100 Worldwide (QS
Subject Rankings 2018, 2019, 2020, 2021).
The research assistant is expected to assist the team with fundamental research and engineering problems, supporting publications in top-tier computer vision and computer graphics conferences (CVPR, ECCV, ICCV, SIGGRAPH) and journals (TPAMI, IJCV). Other responsibilities include supporting graduate or undergraduate students with technical implementations and engagement in other research activities such as reading group, workshop organization, etc.
The start date for the position is flexible, with a preferred start in early 2025. Contract
duration is 1 year with the option of renewing for a second year.
Internship Opportunities
The ClearWay1 project at TCD is exploring ‘slot-based driving’ (SBD) as a strategy for active management of roads. SBD abstracts traffic as flows of slots with each slot having a specified trajectory. Vehicles are associated to slots and their trajectories are intended to follow those of their assigned slots. In practice, depending on the level of control available and/or the degree of compliance of drivers with guidance, vehicles may depart from their slots. However, slots provide an abstraction over which the road traffic management system can reason and exercise control. In particular, we are exploring the use of reinforcement learning to have controllers learn appropriate slot-management strategies.
Internship project: Model-based RL for Autonomous Driving
This project will investigate applicability of model-based RL (MBRL)2 in transportation and
autonomous driving.
Skills required:
Excellent computer programming skills in Python as well as previous experience of autonomous driving simulators and reinforcement learning.
Application details:
The positions are full-time and tenable immediately for up to twelve weeks (expected to finish no later than the 31st of August 2025). As full-time positions, applications from continuing students enrolled in full-time courses who have coursework to complete over the summer months (e.g., a dissertation) are not eligible.