Internship description:
Role closes– 22nd of June
£8.91 per hour (national living wage)
There is an exciting opportunity of two 2-months internships at the MRC Biostatistics Unit (BSU), University of Cambridge within the Design and Analysis of Randomised Trials (DART) theme under supervision of Dr Pavel Mozgunov and Dr Helen Barnett. The internships are funded by the NIHR Methodology Internships grant and aimed at providing undergraduate and graduate students with an experience of a statistical methodologist in medical research.
The interns will work on a real-life problem of designing of a Phase I dose-escalation study motivated by an ongoing trial in COVID-19 treatments. They will learn on how to study the existing statistical literature, how to link it with the research questions stated by the clinical team, how existing statistical methods can be tailored for the need of the specific clinical trial, and how to implement it in the statistical software. By the end of the internship, there will be an opportunity to inform a better decision-making in actual trials.
The interns will learn about the day-to-day activities of a statistical methodologist in clinical trials and will meet with various members of staff across of BSU themes to learn about possible career paths of a methodologist. They will also attend various group meetings across the BSU and will have an opportunity to learn about future career opportunities.
The internship will take place July-August 2021 and will be full-time working Monday – Friday and will take place remotely.
About Host:
The MRC Biostatistics Unit is one of Europe's leading biostatistics research institutions. Our focus is to deliver new analytical and computational strategies based on sound statistical principles for the challenging tasks facing biomedicine and public health. The Design and Analysis of Randomised Trials (DART) theme of the BSU that focuses on the development and implementation of more efficient clinical trial designs in practice. Beyond DART, the interns will also benefit from 3 more research themes within the BSU: Precision Medicine and Inference for Complex Outcomes, Statistical Omics, Statistical methods Using data Resources to improve Population Health.
Dr Pavel Mozgunov is an Advanced NIHR Research Fellow in Medical Statistics with an experience of developing bespoke clinical trial designs and their application in practice. Dr Mozgunov provides statistical support in a number of trials (both publicly and privately funded), including AGILE-ACCORD (https://www.agiletrial.net/), an early phase trial studying novel therapies for COVID-19 treatments. Dr Helen Barnett is a Research Associate working on response-adaptive trials, with specific works on inference for bandit-based designs. Dr Barnett also carries out research in dose-finding studies, with a current focus on designs incorporating late-onset toxicities.
Selection Criteria:
There are three core criteria for the intern selection:
• the statistical/mathematical knowledge (second and third year undergraduates in Mathematics and/or Statistics programmes),
• an interest in the methodological research with application in medical research, and
• programming skills in R.
There are be no pre-requirements of clinical trials or medical statistics knowledge. While these are welcome, the purpose of the internship is to bring the interns with various backgrounds into the medical statistics and to the methodological research. A brief training on clinical trials will be provided if required.
The internship will be administered via Temporary Employment Service and selected workers will be required to registered with TES before it can commence. These internships are open to students from any University.
The applicants should submit a CV and a cover letter to [log in to unmask] by the 22nd of June 2021. The interviews will take place on the week commencing the 21st of June 2021. The cover letter should outline why they have applied for this internship and what they plan to achieve by the end of its completion.
The University has a responsibility to ensure that the selected candidate is eligible to live and work in the UK.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
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