Quantitative & Computational Social Sciences - Research

This programme is built around quantitative and computational social science methods and tools applied to substantive and methodological research questions in the social sciences. The programme brings together the perspectives and research methods of various disciplines such as Economics, Politics, Sociology and Statistics. The QCSS programme provides students with rigorous training in quantitative research and methods, including quantitative text analysis, machine learning, computer vision techniques, agent-based modelling, network analysis, and causal inference. Students will apply these methods in their PhD thesis to answer substantive research questions in Social Sciences.

Successful candidates are invited to join the Connected_Politics Lab, an interdisciplinary hub for researchers using computational methods to study politics and society, the UCD Geary Institute for Public Policy, and/or the (opens in a new window)UCD Behavioural Science and Policy group, a centre for research and collaboration on integrating behaviourally-informed ideas into public policy.

Students with a quantitative background in any area can undertake the programme. They will undertake various quantitative social science modules offered by the UCD School of Politics and International Relations, the School of Sociology, and the School of Economics. They may also choose modules that are relevant to their own research interest in other UCD Schools.

The PhD QCSS programme is a thematic, structured programme.
Doctoral studies at UCD comprise two stages:

Stage 1 is a period when you define your research plan, develop your research skills and initiate original research work for your doctorate.
Stage 2 is primarily dedicated to continuing your original doctoral research but may also include some advanced education and training.

Modules
Note: the modules listed here are for 2023-24. These may change for 2024-25.
All students must take the following module:

POL50220 Social Science Methodology (Core)
All students take at least one of the following three modules:

SOC40640 Social Simulation: Methods and Models
POL42050 Quantitative Text Analysis
ECON50580 PhD Econometrics

In addition, all students take at least three modules, totalling to at least 15 credits. Students with a technical background (computer science, engineering, statistics) take these modules from relevant offerings in the social sciences, while students with a social science background (incl. business and law) take these modules from relevant offerings in computer science, mathematics, and/or statistics.

ACM40290 Numerical Algorithms
COMP40730 High Performance Computing
PLAN40220 Geographical Information Systems
POL42340 Programming for Soc Scientists
SOC40640 Social Simulation: Methods and Models
STAT40400 Monte Carlo Inference
STAT40680 Stochastic Models
COMP47670 Data Science in Python
COMP40610 Information Visualisation
COMP41680 Data Science in Python
COMP47470 Big Data Programming
POL50050 Quantitative Methods II
SOC40690 Demographic Analytics: T & A
SOC41030 Sciences, Technologies & Societies
STAT30270 Statistical Machine Learning
STAT40150 Multivariate Analysis
SOC41070 SocThinking in the Digital Age
SOC41130 AI and Society
SOC30380 Social Dynamics and Networks

The range of modules is subject to change.

The students may register for other modules depending on their research theme with permission from their Supervisor and the Module Coordinator.

The College of Social Sciences and Law schools also make a range of modules available to graduate research students outside their school each year.

A formal Stage Transfer Assessment (STA) takes place in order to progress from Stage 1 to Stage 2 of the PhD. The STA should be completed within 5 trimesters for a full-time student or 7 for a part-time student. Students must submit a body of written work to a review panel, who will conduct an interview on the work submitted, and must also complete a Research and Professional Development Planning (RPDP). For more information on the RPDP click here.

The PhD may take the form of a traditional thesis, or a collection of papers (including published papers or papers submitted or prepared for submission) describing a coherent programme of research that has been published or prepared for publication in peer-reviewed journals of international standing, accompanied by a critical and theoretical overview of the work presented in the papers.

UCD/TCD Collaboration
SPIRe collaborates with the Department of Political Science in Trinity College Dublin (TCD). We currently share modules on quantitative and qualitative research methods. In addition, TCD operates a Maths and Coding Bootcamp for incoming students, as a preparatory course for Quants I.

Students enrolling on the QCSS programme are welcome to attend one or both camps. These usually take place prior to the start of term.

For the structured PhD programme in Quantitative and Computational Social Science, applications are welcomed from applicants with a Master’s degree in data science, computer science, quantitative political science, economics, statistics, and other social science subjects. Applicants to our research degree programmes must have completed and earned a minimum of a 2.1 grade (GPA: 3.6) in a taught Masters (MA, MSc, MLitt, etc.) programme.

When Can I Apply?
There are three application deadlines for the Quantitative and Computational Social Science programme:

Applicants to the Iseult Honohan Doctoral Scholarship: 9th February 2024
IRC Government of Ireland Doctoral Scholarship 2025 applicants: 8th September 2024
All other funded applicants: a rolling deadline between 1st October 2023 and 31st July 2024 (for non-EU applicants the deadline is 30th June 2024)
Note: The Quantitative and Computational Social Science PhD programme only accepts students who have a Honohan Doctoral scholarship, an IRC scholarship or alternative external funding, to include a full fee remission and appropriate living expenses. Self-funded applicants are not eligible.

Duration: 3-4 Years Full Time
5-6 Years Part Time

Entry to the programme is in September only.