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Research Associate in Bayesian Non Parametric at Imperial College London

The International Society for Bayesian Analysis

London

On-site

GBP 40,000 - 60,000

Full time

30+ days ago

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Qualifications

  • PhD in Statistics or related field required for advanced research.
  • Experience in Bayesian methods and causal inference is essential.

Responsibilities

  • Develop novel Bayesian Non-Parametric Tests for Conditional Independence.
  • Collaborate with leading researchers in statistics and machine learning.

Skills

Bayesian Non-Parametric Statistics
Causal Discovery
Machine Learning
Statistical Analysis

Education

PhD in Statistics or related field
Master's in Mathematics or Statistics

Tools

Statistical Software (e.g., R, Python)
Data Visualization Tools

Job description

Research Associate in Bayesian Non Parametric at Imperial College London

Jul 20, 2018

Research Associate in Statistics

Applications are invited for a Research Associate position in the Department of Mathematics at Imperial College London to work in the area of Bayesian Non-Parametric statistics. The position is funded through the EPSRC Grant EP/R013519/1. The Research Associate will work directly with Dr Sarah Filippi and in collaboration with Prof Chris Holmes (Alan Turing Institute).

The post holder will work on developing a novel Bayesian Non-Parametric Test for Conditional Independence. This is at the core of modern causal discovery, itself of paramount importance throughout the sciences and in Machine Learning. In particular, the discovery of causal relationships is fundamental in public health and epidemiology, in life and earth sciences, in sociological studies and in econometrics.

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Research Associate in Bayesian Non-Parametric statistics at Imperial College London

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