Sort by
Refine Your Search
-
protocols for electrical biasing of samples in the microscope. A key task is to process and analyse large 4D-STEM data sets and extract information about domain wall structure and dynamics. The role involves
-
the effectiveness of anticipatory cash transfers in response to climate disasters, using large-scale RCTs in Bangladesh and other countries. It investigates how early interventions can mitigate the impacts of extreme
-
such approaches would be cost effective. To achieve this, you will be supported to undertake analyses using large data registries such as the Clinical Practice Research Datalink. This is an exceptional opportunity
-
Responsibilities for the role include: Data collection, cleaning, and merging from large-scale microdata sources (e.g., patents, dissertations, bibliometrics). Conduct data analysis using econometric and statistical
-
made. The project will involve using routinely collected healthcare data and/or large healthcare datasets such as the Clinical Practice Research Datalink. This is an excellent opportunity for someone
-
quantitative data analyses. The role involves co-ordinating a large study and liaising with clinical participants, so the ideal candidate would have exceptional interpersonal and organisational skills. Further
-
Assistants is £32,546 - £35,116 and for Research Associates this is £37,174 - £45,413 per annum. Suitable candidates should have previous experience of genetic analysis of large scale genome sequence data and
-
theory, and the analysis of large data ensembles. You will write papers for submission to academic journals, collaborate with academics and PhD students, and communicate your research at national
-
optimization techniques, coding new algorithms, creating new mathematical theory, and the analysis of large data ensembles. You will write papers for submission to academic journals, collaborate with academics
-
One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour