Upload your CV
Go to job search

Research Associate in Modern Statistics, Global Health, and Conservation Ecology

Imperial College London, City of London

Research Associate in Modern Statistics, Global Health, and Conservation Ecology

Salary not available. View on company website.

Imperial College London, City of London

  • Full time
  • Temporary
  • Onsite working

Posted 3 days ago, 2 Oct | Get your application in today.

Closing date: Closing date not specified

Job ref: d2ca787fc31e4495a6aa61d45fdb75ad

Location ref: City of London

Full Job Description

Research Associate in Modern Statistics, Global Health, and Conservation Ecology


2026-09-29T00:00:00


City of London


Greater London


GB


EC4N 6JD


Any


2026-12-28T19:00:53.943


Research Associate in Modern Statistics, Global Health, and Conservation Ecology


Jul 24, 2023


Salary Range: £43,093- £50,834 per annum


Fixed Term for initially 12 Months with extension likely


Start date: 1 October 2023 or soon thereafter


This is an exciting opportunity to help lead an ongoing programme of methodological research to tackle pressing global health problems in collaboration with leading international organisations.


The focus of this post is on the development of novel, flexible and computationally tractable spatio-temporal statistical inference tools in Bayesian Statistics and AI, and on their application in three domains. Applications range from HIV deep-sequence phylogenetics within the PANGEA-HIV consortium, to quantification and hotspot mapping of caregiver loss with the Global Reference Group for Children Affected by COVID-19 and in Crises, and species mapping and forecasting using oceanographic and climatological datasets.


You will have access to some of the finest longitudinal datasets in Africa and South America. Post holders will interact with a team of leading researchers. They will receive hands-on training in machine learning and modern statistics, epidemiological, and phylogenetic techniques, and will be mentored by leading scientists, who often publish in some of the top journals of the field.


Your base will be in the Department of Mathematics at Imperial College London, and you will work closely with the Machine Learning & Global Health Network (MLGH), a multi-institution research laboratory with members at Oxford, Imperial College London, University of Copenhagen, and Singapore. Post holders will be reporting directly to Dr Oliver Ratmann (Imperial), and collaborating closely with Professor Seth Flaxman (Oxford), Dr Kate Grabowski (Johns Hopkins), Dr Ettie Unwin (Bristol), Dr Adam Sykulski (Imperial), and Professor Christophe Fraser (Oxford).


#J-18808-Ljbffr


#s1-Gen

Research Associate in Modern Statistics, Global Health, and Conservation EcologyJul 24, 2023Salary Range: £43,093- £50,834 per annum Fixed Term for initially 12 Months with extension likely Start date: 1 October 2023 or soon thereafterThis is an exciting opportunity to help lead an ongoing programme of methodological research to tackle pressing global health problems in collaboration with leading international organisations.The focus of this post is on the development of novel, flexible and computationally tractable spatio-temporal statistical inference tools in Bayesian Statistics and AI, and on their application in three domains. Applications range from HIV deep-sequence phylogenetics within the PANGEA-HIV consortium, to quantification and hotspot mapping of caregiver loss with the Global Reference Group for Children Affected by COVID-19 and in Crises, and species mapping and forecasting using oceanographic and climatological datasets.You will have access to some of the finest
longitudinal datasets in Africa and South America. Post holders will interact with a team of leading researchers. They will receive hands-on training in machine learning and modern statistics, epidemiological, and phylogenetic techniques, and will be mentored by leading scientists, who often publish in some of the top journals of the field.Your base will be in the Department of Mathematics at Imperial College London, and you will work closely with the Machine Learning & Global Health Network (MLGH), a multi-institution research laboratory with members at Oxford, Imperial College London, University of Copenhagen, and Singapore. Post holders will be reporting directly to Dr Oliver Ratmann (Imperial), and collaborating closely with Professor Seth Flaxman (Oxford), Dr Kate Grabowski (Johns Hopkins), Dr Ettie Unwin (Bristol), Dr Adam Sykulski (Imperial), and Professor Christophe Fraser (Oxford). #J-18808-Ljbffr

Direct job link

https://www.jobs24.co.uk/job/research-associate-in-modern-statistics-global-health-127499966
Relevant jobs