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Building bridges between science and policy through the Royal Society ‘pairing scheme’
19 March 2024
PML is taking part in the annual initiative to give scientists an insight into UK policymaking.
Above: Our Modelling Scientist, Deep Banerjee, pictured in front of the Houses of Parliament
Modelling Scientist, Deep Banerjee from Plymouth Marine Laboratory (PML) is one of 30 UK scientists taking part in the prestigious Royal Society Pairing Scheme, designed to help build long-term relationships between scientists and politicians and ensure that policymakers can make informed decisions based on the best scientific evidence.
As part of the annual initiative, participants are being given a behind-the-scenes insight into how policy is formed, shadowing an MP or parliamentarian to learn about their work. They will hear from senior civil servants and parliamentarians on how research findings are used to inform policymaking and how they can best share their expertise with policymakers. As part of the 2024 scheme, Deep is paired with Luke Pollard, the MP for Plymouth Sutton and Devonport and Shadow Minister for Defence.
Above: Luke Pollard MP (left) with Deep Banerjee (right)
The week began with a parliamentary reception in the House of Commons, including speeches from Greg Clark MP (Chair of the Commons Science and Technology Committee), Andrew Griffith MP (Minister of State for Science, Research and Innovation) and Sir Adrian Smith, President of the Royal Society.
Scientists taking part in the pairing scheme this year are drawn from universities and research institutes across the UK. In addition to PML these include Newcastle University and Imperial College London. They are paired with parliamentarians including Chi Onwurah MP (Shadow Science Minister); Baroness Brown of Cambridge FRS (member of the House of Lords and Chair of its Science &Technology Committee); and civil servants from the Department for Education; Energy Security and Net Zero; and Business and Trade.
“I’m extremely proud to be taking part in the pairing scheme, and the chance to get some valuable insight into the science-policy interface,” said Deep.
“It’s really important to me that my science has impact and so I’m looking forward to learning more about how UK policy can be informed and driven by the work undertaken by scientists like myself. I’m also really excited about spending time with Luke Pollard and his team, getting an understanding of the work involved being an MP and helping to improve the way we can inform policymakers.”
The scheme continues later in the year when parliamentarians visit their paired scientist at their home institutions. Previous participants from PML include Dr Lee De Mora (2023), Dr Liz Talbot (2022), Dr Matthew Frost (2017), and Dr Caroline Hattam (2015).
Above: Deep chatting with Greg Clark MP, Chair of the Science, Innovation and Technology Select Committee.
Above: Members of this year’s pairing scheme cohort at the Houses of Parliament
Sir Adrian Smith, President of the Royal Society, said:
“Scientific evidence is essential for any government to address many of the global challenges that affect both the UK and world at large, from climate change to the rapid acceleration of AI technologies. The pairing scheme was set up in 2001 to help build bridges between scientists and policy makers, providing them with the opportunity to develop long-term relationships to ensure that robust scientific evidence is used to shape public policy. We must continue to strengthen these collaborations to ensure research is translated into policy that improves the lives of all of those in the UK.”
Related information
Deep serves as a Modelling Scientist at Plymouth Marine Laboratory (PML) in Marine System Modelling division. With his previous eight years’ experience in working with various numerical ocean/sea ice models and data assimilation schemes, Deep is presently developing an Artificial Neural Network-based model in the Atlantic-European North West Shelf domain. This research work aims to improve biogeochemical model forecasts and analyses, with the ultimate objective of providing better predictions related to harmful events such as eutrophication.
Find out more about Deep >>