Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
Development opportunities Pension Scheme with generous employer contribution Various schemes including Cycle to Work, Season Ticket Loans and help with the cost of Eyesight testing. Free parking The successful
-
analysis to join a dynamic team that has, for the past 8 years, developed an extensive body of research on corruption, governance and anti-corruption strategies. In the Accountability in Action project
-
research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models
-
documentation, supporting partners in protocol development and laboratory set up and training before and during the clinical trials. The post-holder will also be expected to contribute to ad-hoc activities
-
possible thereafter). In return we offer a highly competitive rewards and benefits package including: Generous annual leave entitlement Training and Development opportunities Pension Scheme with generous
-
vaccination barriers and facilitators, develop forecasts of vaccine coverage for existing and novel vaccines (e.g. HPV, RSV, malaria), and support the design and implementation of small area estimation and
-
, and OpenSAFELY, and to develop and apply the new generation of analytical methods to study environmental health risks and climate change. The post will provide opportunities for interactions with
-
range of personal and professional development opportunities. In addition, we offer a range of work life balance and family friendly, inclusive employment policies, flexible working arrangements, and
-
develop research that can inform policy in this important area. The candidate should have a background in a quantitative subject, in particular epidemiology or medical statistics and be familiar with
-
, development, implementation, and coordination of research and laboratory protocols to investigate transmission of enteric pathogens in low-income households of Salvador, Brazil within the context of large-scale