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.
/prod01/channel_3/media/tcd/scss/images/vacancies.jpg)
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 Maintenace & 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 and the ARIA programme, to Professor Gregory O’Hare Gregory.OHare@tcd.ie with a subject heading ARIA Application.
Fine-tuned for computer programming tasks, generative AI coding assistants, of which GitHub Copilot is a well-known example, can suggest next blocks of code in a program, find and correct errors, explain and answer questions about programs and create partial or complete programs from scratch when given a natural language prompt.
Although imperfect, the capabilities demonstrated by AI coding assistants have prompted widespread discussion and debate about the future of computer programming education and even the future of programming itself [1] [2].
There is an emerging concern that using AI coding assistants can negatively affect learning that occurs during programming activities, whether in educational, informal, or professional settings.
The successful candidate for this position will explore how future AI coding assistants might be designed to promote learning, while also recognising that the nature of computer programming is changing. The project will draw inspiration from – and contribute to – the growing body of literature exploring the effects of generative AI and coding assistants on learning by programmers. Central to the project will be the design, implementation and evaluation of technical innovations in the implementation of AI coding assistants to promote learning.
This funded 4-year position includes:
• an annual stipend of €22,000 (for 4 years), and
• fees to pursue a PhD in Computer Science (for 4 years, at the fee level charged to EU students).
Deadline of 31 January 2025 for applicants who wish to begin before September 2025
Motivation. Modern AI/ML-enabled Software Systems, consisting of multiple AI/ML components and related traditional software components, face numerous engineering challenges beyond the basic performance of single AI/ML components. When designing such systems and the related AI/ML pipelines, engineers have to deal with a large number of design decisions balancing multiple competing objectives, e.g., performance, robustness, and more complex goals like user experience, explainability, and trustworthiness. This creates a complex design space that needs systematic exploration and optimization approaches.
Focus. The successful candidate for this position will investigate novel approaches to design space exploration and optimization for AI/ML-enabled systems. The research will focus on developing methods and tools to help engineers make better design decisions when building and improving complex AI/ML-enabled systems, considering multiple competing objectives. Of particular interest are approaches that provide automatic and interactive tool support to deal with the whole configuration space as a whole.
Position. This is a funded 4-year PhD position and includes:
• an annual stipend of €22,000 (for 4 years), and
• fees to pursue a PhD in Computer Science (for 4 years, at the fee level charged to EU students).
Deadline of 31 January 2025 for applicants who wish to begin before September 2025
Overview: Smart contracts are transforming how we can enhance automated public services and how
the services are executed and controlled in digital ecosystems. Distributed artificial intelligence (AI) is a new AI paradigm that uses distributed device computing resources to improve data privacy. The
combination of smart contracts and distributed AI has the potential to address challenging research
issues, including data privacy, security, and network scalability, thus fostering efficient and responsible actions for reliable digital transformation ecosystems. Although promising, there is no high-level
reference framework for designing novel smart contract driven distributed AI solutions and a lack of
benchmarking testbeds for essential use cases and scaling their implementation internationally.
Focus and role: The successful applicant for the position will investigate innovative approaches using smart contracts and distributed learning to improve public digital services in smart cities and 6G. The
research will primarily focus on developing 1) reliable distributed AI models for optimising resource
allocation and misbehaviour detection in connected applications, 2) decentralised AI solutions to
improve security protection and privacy preservation of interconnected smart cities, and 3) personalised learning solutions for hyperconnected digitalization systems (including 6G). Of particular interest is the demonstration of the developed solutions in O-RAN and Hyperledger-based 6G networks.
Position: The position is fully funded for 3 years. The successful applicant will receive:
• an annual stipend of €22,000 (tax-free, for 3 years), and
• an annual PhD fee of €5,500 fee to pursue a PhD in Computer Science.
Closing Date: 28th February 2025
Research Opportunities
Post Summary
We are seeking to recruit two post-doctoral research fellows to investigate novel reinforcement learning (RL) algorithms and their applications in IoT and edge cloud networks, within CONNECT - the Science Foundation Ireland Research Centre for Future Networks and Communications.
Position 1 (IoT networks): This project will investigate the use of multi-agent RL for sensor-scheduling in energy-constrained environments. Developed algorithms will need to be lightweight and are required to run on energy and resource-constrained devices. Algorithms will utilize Age of Information metric to learn appropriate update interval, taking advantage of observed correlation to reduce sensor system energy usage.
Position 2 (edge cloud networks): This project will investigate the use of multi-agent and multi-objective RL for optimisation of resource allocation in edge cloud networks.
The successful candidates are expected to make contributions to the state of the art in RL algorithms and their applications in communication networks.
The positions will be based in the CONNECT Research Centre at Trinity College Dublin, Ireland under the direction of Dr. Ivana Dusparic, working in close collaboration with colleagues at other CONNECT partner Universities. In particular, position 1 will be involved close collaboration with Tyndall Institute, utilizing their renewable energy testbed.
For informal inquiries please contact ivana.dusparic@tcd.ie.
CLOSING DATE: 20th December
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