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Doktorand i maskininlärning

Uppsala, Sweden💼 Full-time🗓 2026-09-23 → 2026-09-26

Core

Developing new methods for uncertainty quantification in mathematical and statistical models applied to large-scale clinical cancer data.

Role type

PhD researcher (Data-driven precision medicine and diagnostics)

Builds

Probabilistic models predicting time-to-event based on medical reports and clinical data

Domain

Data science, applied mathematics, statistics, oncology

Deliverable

production ML models

Required skills

linear algebra, probability theory, analysis, programming, applied mathematics, statistics

Preferred skills

Bayesian statistics, mathematical modeling, statistical machine learning

Responsibilities

Conduct independent research on uncertainty quantification methods, apply methods to clinical cancer data, quantify uncertainty in information extracted from medical reports

Seniority

PhD candidate (early career researcher)

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