Publisher
source

Trinity College Dublin

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PhD Scholarship

PhD Scholarship in Decision-Focused Learning, Model Multiplicity and Causal Recourse in Financial Services Trinity College Dublin in Ireland

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available
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Country

Ireland

University

Trinity College Dublin

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Keywords

Computer Science
Information Technology
Mathematics
Business
Causal Inference
Optimisation
Economics
Statistics
Machine learning

About this position

PhD Scholarship opportunity in Decision-Focused Learning, Model Multiplicity and Causal Recourse in Financial Services at Trinity College Dublin, Ireland.

The project is looking for candidates with a background in statistics, mathematics, or a closely related field. A Master’s degree is desirable but not essential. Strong theoretical and practical statistics skills are expected, along with solid programming ability. Helpful experience includes machine learning, optimisation, causal inference, fairness, explainable AI, and financial applications.

Applicants should prepare a PDF package containing a cover letter, CV, undergraduate and postgraduate transcripts, English language certification if required, and the names/contact details of two academic referees. The application should be emailed to Dr. Mimi Zhang at [email protected] with the specified subject line.

Trinity’s postgraduate admission requirements note that applicants generally need at least a 2.1 honours degree or equivalent and must meet the university’s English language requirements. Shortlisted candidates are expected to be contacted during the week beginning 25 May 2026, with interviews during the week beginning 1 June 2026.

This is a strong fit for students interested in statistical learning, causal decision-making, and responsible AI methods applied to finance.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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