Qualification Type: | PhD |
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Location: | London |
Funding for: | UK Students, EU Students, International Students |
Funding amount: | £22,237 annual stipend |
Hours: | Full Time |
Placed On: | 20th December 2024 |
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Closes: | 10th January 2025 |
Applications are invited for up to 5 PhD Studentships and 1 Studentship on project "Causality for Healthcare AI" supervised based at the Department of Statistical Science, UCL. The positions can involve any topic within the Statistical Science remit.
The Department is among the three largest Statistics groups in the UK with more than 30 academic members of staff. Research in the Department is organised into six themes.
The positions can involve any topic across the field of Statistics and are open to Home and International applicants, subject to an overall cap on the number of International positions that can be funded. Each Studentship provides funding for 3.5 years (or 6 years for part-time students).
Each Departmental Studentship will be 3.5 years in duration (or 6 years for part-time students) and will cover the full tuition fees, an annual maintenance stipend (this was £22,237 for 2024/25, with some rise expected to be applied for 2025/26 and for each of the subsequent years during the PhD) and an allowance for research training.
1 Studentship for a 4-year "Causality for Healthcare AI" PhD project to be supervised by Professor Ricardo Silva. The project will involve methodological topics in causal inference and machine learning, with applications to healthcare. The position is full-time only.
Person Specification
The requirement for admission to the MPhil/PhD in Statistical Science is a 1st class or high upper 2nd class Bachelor’s degree, or a Master’s degree with merit or distinction, in Mathematics, Statistics, Computer Science, or a related quantitative discipline. International qualifications of an equivalent standard are also acceptable. Further details can be found on the Departmental website.
Applications must be submitted by the deadline of 10th January 2025, with shortlisting decisions made very soon after this date.
Interviews are expected to take place in late January or beginning of February.
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