The College of Life Sciences offers a dynamic, modern environment for study and research, built on decades of highly respected achievement. The College has nearly a thousand staff and approaching 4,000 students across it’s departments, which includes Population Health Sciences, and Respiratory Sciences where this post will be based.
The purpose of this fixed term post is to increase research capacity in child and perinatal health, with a focus on the utilization of large real-world datasets to answer clinically important Paediatric and Neonatal research questions.
You will work collaboratively and independently as part of a research team to achieve defined milestones and produce high quality research as part of a wider programme. You will also be encouraged and supported to develop and apply for further grant/fellowship funding to further their personal development and ongoing employment within academia.
You will bring to the role an in-depth knowledge of statistics, gained either through a relevant higher degree at MSc or PhD level or extensive relevant professional experience and qualifications. You must have robust knowledge of fundamental statistical methods and principles and/or machine learning techniques and be competent in statistical software, such as R, Python and/or STATA. You should have experience of pre-processing/cleaning, integrating/linking and analyzing real world data sets, couple with experience working with complex ‘big data’ such as clinical data or large scale bioinformatics data.
You will be a confident communicator, able to communicate complex information to multidisciplinary audiences, write concise and clear analysis and reports and be confident contributing to scientific discussions and the critical exchange of ideas. Excellent interpersonal skills are also essential to develop strong working relationships with scientists and academics from complementary disciplines to develop collaborative research.
Informal enquiries are welcome and should be made to David Lo (firstname.lastname@example.org) and Professor Lucy Smith (email@example.com)