Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
. You will hold a relevant BA or MSc degree in Mathematics, Engineering, or a related field. Knowledge of medical statistics and experience analysing large datasets, experience in biostatistics and/or
-
. You will hold a relevant post-graduate degree in Epidemiology or a related field together with experience in biostatistics and/or health data sciences. Experience in programming statistical analyses
-
. Experience in MS data analysis and statistics (i.e. MaxQuant, Perseus, and Prism) is desirable. Applications for this vacancy are to be made online and you will be required to upload a supporting statement and
-
methodologies and contribute ideas for new research projects. To be considered, you must hold a higher degree (e.g. MSc/PhD) in epidemiology, statistics or a related subject, have significant relevant experience
-
for Cancer Research, University of Oxford In this role your duties will include provide statistical analysis plans for studies and handle day-to-day planning to keep the work on track and efficient and the
-
Student Data Management & Analysis (SDMA) team provides a portfolio of data, reporting and statistical services for the University of Oxford, in addition to maintaining and facilitating access to reporting
-
pathways. You will also have the freedom to determine your own research approaches within this broad framework. You will have or be close to the completion of a PhD in statistical/computational genomics with
-
Applications are invited for a Quantitative Research Assistant to work within the Medical Statistics team under Rafael Perera and Patrick Fahr on a climate change and health research programme. The
-
project that will enhance Population Health research in Oxford. Applicants should have an MSc in a subject relevant to Population Health (e.g. medical statistics, epidemiology, health economics, sociology
-
Hollingsworth’s group is a world leader in the development of statistical, mathematical, and computational models that inform disease dynamics and the translation of outputs to national and global health policy