Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oxford
- ;
- KINGS COLLEGE LONDON
- King's College London
- University of London
- Durham University
- Heriot Watt University
- UNIVERSITY OF VIENNA
- University of Cambridge
- Nature Careers
- University of Oxford;
- AALTO UNIVERSITY
- Birmingham City University
- DURHAM UNIVERSITY
- Heriot-Watt University;
- Imperial College London
- King's College London;
- Liverpool School of Tropical Medicine;
- Northumbria University;
- Oxford Brookes University
- Oxford Brookes University;
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Technical University of Denmark
- University of Bath
- University of Birmingham
- University of Cambridge;
- University of Exeter
- University of Exeter;
- University of Lincoln
- University of Manchester
- University of Nottingham
- University of Nottingham;
- University of West London
- 23 more »
- « less
-
Field
-
colleagues. We put special emphasis on a flexible and cooperative working environment. Social interactions help facilitate active scientific exchange and foster a good atmosphere, and therefore play a big role
-
considered. The successful candidate must have experience in the following areas: molecular cell biology, plant phenotyping, and image/data analysis, as well as working as part of a large team. A track record
-
R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
-
facilities such as microscopy, SEM, cavitation erosion and fatigue testing, micro/nano-indentation etc. is required. In addition, handling and processing of large data sets, knowledge of data acquisition
-
at command line and BASH scripting Experience working with large scale, complex datasets and data wrangling skills Strong publication record and familiarity with the existing literature and research in
-
at command line and BASH scripting Experience working with large scale, complex datasets and data wrangling skills Strong publication record and familiarity with the existing literature and research in
-
to analyse datasets 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
-
will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and help supervise associated PhD students. The successful candidates will join large, supportive
-
related field together with strong programming skills in Python, R, or similar languages, and proficiency in high-performance computing. You will have experience in large-scale genomic data analysis. You
-
of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles