-
. Stata, R, SAS), experience in statistical analysis of medical data and a good understanding of statistical methods such as regression and GLMs. In return we offer an excellent benefits package including
-
wearable devices into the existing remoting monitoring system, and the integration of algorithms for automatic analysis of data received at the backend. About You You should hold a MSC degree in a relevant
-
able to explain complex financial or regulatory matters in simple and understandable terms. Excellent numeracy skills are essential as is confidence in financial data analysis and proficiency in using
-
completion of these studies is an essential requirement of this Apprenticeship. In total, it will take 2 years to complete all elements of the apprenticeship, with support from the Department, University and
-
analysis skills and experience in statistical modelling, data wrangling, and analysis of complex behavioural datasets using R, Stata, or other statistical software packages. Experience of developing
-
development or custom device fabrication is essential. Familiarity with Drosophila melanogaster as a model organism is highly desirable, especially in the context of behaviour or neural circuit analysis
-
of working on epidemiological analysis of the UK Biobank. This role will involve working with Co-Is Professor Melinda Mills and Associate Professor Charles Rahal, and with a wider team in the Demographic
-
/ computational biology / life sciences discipline, or relevant field such as computer science, mathematics or statistics. You will have substantial experience in the analysis of large datasets, which will allow
-
Service and Reporting Specialist, this role requires both technical expertise and business analysis skills to identify requirements, design solutions, and drive continuous improvements in IT service
-
assays, cell culture techniques, and biological data analysis. You will possess strong organisational skills with the ability to manage resources, time, and priorities effectively. You will have highly