Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- University of Oxford
- ;
- KINGS COLLEGE LONDON
- UNIVERSITY OF VIENNA
- University of Oxford;
- AALTO UNIVERSITY
- Aston University
- Durham University
- Heriot Watt University
- UNIVERSITY OF READING
- University of Liverpool
- CZECH UNIVERSITY OF LIFE SCIENCES
- DURHAM UNIVERSITY
- King's College London
- NORTHUMBRIA UNIVERSITY
- Northumbria University;
- Nottingham Trent University
- Oxford Brookes University
- The University of Edinburgh;
- University of Cambridge
- University of Cambridge;
- University of Durham
- University of Essex;
- University of Exeter
- University of Exeter;
- University of Lincoln
- University of London
- University of Manchester
- University of Newcastle
- University of Reading
- University of Sheffield
- 21 more »
- « less
-
Field
-
further including to automated platforms to generate large statistical data sets. We will also experiment with untried higher spatial resolution techniques. The large, multi-dimensional data sets will be
-
specialist knowledge in a relevant subject area. With knowledge of statistics and ability to use statistical packages for analysing data, you will have excellent communication skills and the ability to work co
-
specialist knowledge in a relevant subject area. With knowledge of statistics and ability to use statistical packages for analysing data, you will have excellent communication skills and the ability to work co
-
. Proficiency in the use of statistical programming languages and analysis of large datasets and strong publication records would be essential. Previous experience in atmospheric dynamics and predictability is
-
Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate
-
research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
-
research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
-
analysis of data from a Nipah virus vaccine trial, using machine learning and statistical tools to identify immune response markers for future trials. You will be responsible for developing new and adapting
-
of mole activity and soil health and biodiversity, collecting data on visitor perceptions of moles and their management, and analysing findings using statistical modelling approaches. The role provides
-
available option. Applicants with a range of academic subject backgrounds are welcomed, including natural sciences, engineering, statistics and applied mathematics with experience and/or growing interest in