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Sofya Titarenko

Top university

4 months ago

Fully Funded PhD in Applied Statistics, Epidemiology and Data Science at University of Leeds University of Leeds in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded PhD opportunity for home students.

Deadline

Expired

Country flag

Country

United Kingdom

University

University of Leeds

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Keywords

Computer Science
Data Science
Epidemiology
Biology
Mathematics
Mathematical Modeling
Infection Control
Salud Pública
Econometric
Statistics

About this position

Fully funded PhD opportunity at the University of Leeds in the areas of statistics, applied statistics, epidemiology, data science, and mathematical modelling.

The project aims to enhance the Farrington algorithm for infection prevention and control, with a focus on spatiotemporal modelling and adaptive modelling approaches. This is a strong fit for applicants interested in quantitative research at the intersection of public health and data-driven methods.

The post is being shared by Sofya Titarenko, Lecturer at the University of Leeds. The opportunity is specifically for home students.

Eligibility highlights include a strong BSc in Mathematics, MMath, or MSc, plus a solid background in mathematical, statistical, or related quantitative methods. The post indicates that the PhD is fully funded.

Application deadline: 30 June.

Interested candidates should review the project description linked in the post and apply before the deadline.

Funding details

Fully funded PhD opportunity for home students.

What's required

Applicants should have a strong BSc in Mathematics, MMath, or MSc, with a solid background in mathematical, statistical, or related quantitative methods. The opportunity is for home students only. Interest in applied statistics, epidemiology, data science, spatiotemporal modelling, and adaptive modelling is relevant.

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Professors

Lecturer

University Name
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United Kingdom

Research Interests

Statistics

Neuropsychology

Salud Pública

Mathematics

Machine Learning