Vacancies

The School of Computer Science and Statistics is seeking to appoint an Assistant Professor in Computer Science, who will join the Discipline of Software and Systems.  The Assistant Professor will be a full faculty member, and as such will be expected to innovate in both research and teaching, to assist in the administration and mission of the School and contribute to the wider research community.

The appointee should have the potential to develop into a leader in their particular field of research with a world-class research programme. The successful candidate will be expected to contribute to undergraduate and/or postgraduate teaching in the School, particularly in areas of Software and Systems.

Closing date is Tuesday 10^th March 2026

Full Details

AI Engineering emerges from a fundamental shift in how we build software systems. Modern applications increasingly embed AI/ML components that generate substantial business value and/or ensure the correct operation of critical systems: Recommendation engines driving e-commerce revenue, LLMs powering intelligent interfaces, computer vision enabling medical diagnosis, predictive models informing financial decisions, and autonomous systems used in safety-critical environments like transportation and healthcare.
Unlike traditional code, where behaviour is explicitly specified through programmed logic, these AI components learn patterns from data, making their behaviour emergent rather than programmed. This fundamental difference introduces new engineering challenges around uncertainty, interpretability, and robustness. The complexity intensifies when multiple models are combined, or multiple AI agents collaborate to achieve intended system objectives, a scenario increasingly common in real-world deployments.

Some examples of potential research areas include:
• Software Engineering for AI-enabled systems: Adapting traditional techniques to handle the inherently different nature of AI/ML components—including requirements engineering for uncertainty, AI-aware software design, testing probabilistic systems and agentic AI systems, and ensuring reproducibility across evolving pipelines.
• Particular challenges arise when engineering approaches need to consider recent developments in AI, which are also under heavy demand in current industry practice, e.g., model refresh, continual learning, trustworthiness of AI, agentic AI, and agents pursuing long-term objectives.
• Optimisation and Metaheuristics: Multi-model, multi-agent, and whole-pipeline optimization, balancing accuracy with computational costs, and systematically exploring high-dimensional configuration spaces to discover non-obvious solutions.
• Model and System Evolution: Detecting and managing data and model drift, triggering appropriate retraining, and developing specialized CI/CD pipelines with statistical validation and rollout/rollback strategies.
• Systems Engineering: Taking a whole-systems perspective that considers interactions across data collection, training, inference, and monitoring—including multi-agent coordination, conflict resolution, and system-level guarantees despite individual agent uncertainty.

Full Details

Deadline: Rolling basis, with a deadline of 31 January 2026 for applicants who wish to begin before September 2026.

Project title: Evaluating the Impact of Generative Artificial Intelligence Tool Use on Student Learning and Assessment

PhD topic: Generative artificial intelligence (GenAI) tools have transformed the educational landscape, with reports stating that over 92% of higher education students are using them. Despite their potential, the use of GenAI tools raises significant concerns regarding academic integrity, ethical and environmental responsibility, skill development, long-term learning, and the potential devaluation of academic qualifications. Empirical research examining the impact of using GenAI tools on student learning remains limited and has yielded mixed findings, creating uncertainty for educators and institutions. 

This project aims to deliver rigorous evidence-based insight into how GenAI use is impacting student learning and assessment in higher education. The project will critically assess the validity, reliability, and effectiveness of different assessment types in light of GenAI. To rigorously assess the educational impacts of GenAI tool use, this project will involve designing and implementing
observational and experimental studies, collecting data, developing novel statistical models,conducting data analysis, and interpreting the results. The project will need to overcome the challenges of observational data, short-term measurement, and uncertain GenAI usage. With a strong commitment to open science and reproducibility, the research will inform evidence-based 
recommendations for the higher education sector.

Project supervisor: Dr. Emma Howard (Trinity College Dublin)
Project location: Discipline of Statistics and Information Systems, School of Computer Science and Statistics, Trinity College Dublin, The University of Dublin, Ireland.

The PhD student will be expected to be a resident in Ireland for the duration of the PhD. 

Application deadline: 8th March 2026
Start date: Anticipated start date is the 1st September 2026
PhD structure: This is a full-time 4-year structured PhD project. The funding for the project includes a tax-free stipend of €25,000 per annum. In addition to the stipend, EU fees (for those who qualify) will be covered for four years.

Full Details

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

Post Summary

The School of Computer Science and Statistics at Trinity College Dublin (TCD) is recruiting a Postdoctoral Research Fellow to work with Prof Khurshid Ahmad on research on investigating the detection and analysis of facial expressions and voice modulations on public domain videos and sound tracks. 

Our Research Ireland project, “FEELING POLITICAL: A comparative investigation of the emotional politics of populist”, will be evaluating systems for extracting emotions from the videos of prominent politicians that have been broadcast already.  The Research Fellow will be working in a team comprising academics and researchers at TCD and Maynooth University.  You will be working in a School with a university, that has been ranked highly in international evaluations in respect of academic and research performance.

Research Responsibilities:

This position is clearly focusing on research.  The chosen candidate should contribute to the creation of new knowledge and publish in high-quality, international peer-reviewed journals . Specifically, this post-doc position focuses on the following responsibilities: 

• Contribute to the design, analysis, and write-up of a method for extracting facial and voice expressions of a set of politicians and correlating the emotions with each other and with economic and social data
• Support the coordination and progress of research collaborations (meetings, reading/writing sessions).
• Provide mentoring and methodological support for PhD students, with opportunities to support supervision activities (as appropriate).

The position may entail participation and/ or management of externally funded research applications and projects.

Full Details