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Official source checkedOpenFully funded
Fully Funded PhD Studentship · January 2027 or earlier

Developing Fair and Robust Cancer Risk Prediction Models Using Health Data

University of Cambridge

A fully funded Home-fee PhD developing equitable cancer-risk prediction models using linked health records, missing-data methods and simulation.

United KingdomOct 1, 2026Last source check Aug 7, 2026
This record is incomplete.Still missing: source evidence. It is published so you can see what is known and what is not, and it is excluded from search indexing until the gaps close.
Confirm current details before applying.Source review was due 10/08/2026. Confirm details on the official page.
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Information needed

  • Your target study level
  • Your field of study
  • Your relevant experience
  • Your language-test status

The provider makes the final eligibility and selection decision. Verify all requirements on the official source before applying.

Meeting every stated requirement does not guarantee selection. The provider makes the final decision.

Funding package

What the opportunity covers

Home tuition fees covered.
£20,780 tax-free per year at the stated UKRI 2026 rate.
Number available: 1

Not mentioned by the official source

  • Mandatory fees
  • Living stipend
  • Accommodation
  • Health insurance
  • Travel

These costs are not addressed in the funding information captured from the provider. That does not mean they are excluded — it means nobody has stated either way. Budget for them, and confirm on the official source.

Eligibility

Who can apply

  • Relevant quantitative, biomedical or laboratory research experience is beneficial. Exact essential experience varies by project.
  • First-class or upper second-class degree or equivalent in statistics, mathematics, computer science, engineering, data science or a related biomedical or population-health field.
  • Applicants eligible for Home tuition fees.
  • See programme-specific entry requirements. Where stated, first-class or upper second-class degree or equivalent.
  • Strong analytical and programming skills, including R or Python. Experience with statistical modelling, machine learning or health data is relevant.
  • Applicants must meet University of Cambridge English-language requirements where applicable.
Application package

Documents and steps

Required documents

  1. Two academic referees, transcripts, CV, English-language evidence where applicable and a statement of interest.

Application steps

  1. Review the official studentship vacancy

  2. Open the named Cambridge course application page

  3. Create a postgraduate applicant account

  4. Quote the vacancy reference and identify the project

  5. Upload all course and studentship documents

  6. Ensure referees submit by the applicable deadline

Evidence and freshness

Sources behind this record

This record was checked against an official provider source. Confirm the final requirements and application route on the official website before applying.

No public evidence excerpt is available yet. Use the linked official source to confirm every material claim.

Not yet recorded from an official source: eligible nationalities, required academic background, language requirements, work-experience requirements, required documents. Unknowns are stated rather than filled with generic advice.

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Application steps

  1. Review the official studentship vacancy
  2. Open the named Cambridge course application page
  3. Create a postgraduate applicant account
  4. Quote the vacancy reference and identify the project
  5. Upload all course and studentship documents
  6. Ensure referees submit by the applicable deadline

This checklist is a personal preparation aid. Always verify current requirements on the official provider website before submitting your application.

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Scholarship · 2026 application cycle for 2027 study

Massey University Doctoral Scholarship

Massey University

Doctoral scholarship supporting high-achieving candidates enrolling in eligible doctoral programmes at Massey University.

New ZealandDoctoral, DoctoralOct 1, 2026
Checked Aug 29, 2026Official source