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Scientific research and development

Guidance and regulation

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  • Calls for new funding opportunities in development research run by the Foreign, Commonwealth & Development Office (FCDO) or our development partners.

  • Putting geological disposal into context

  • Guidance for suppliers of science and technology research who sign up to R-Cloud and R-Cloud+ to access opportunities from across the Ministry of Defence (MOD).

  • Successful applications that will progress to the next stage of the Research Ventures Catalyst programme to stimulate the creation of novel research ventures.

  • Dstl ensures the UK armed forces have the required weapons capability through research, development and demonstration of advances in science and technology.

  • BEIS is providing up to £2.5 million in innovation funding to support the development and demonstration of High Temperature Gas Reactor (HTGR) technology in the UK.

  • Research, design, delivery and analysis of wargames, to provide insights and support decisions in UK defence and security.

  • A short guide to artificial intelligence (AI), data science and machine learning, explaining the terminology and helping you use and apply the latest advances.

  • A summary of UKAEA's approach to social value and the supply chain

  • Opportunity to license Dstl technology: game that can be used to help improve cyber resilience.

  • Information for the UK Atomic Energy Authority’s JET Decommissioning and Repurposing (JDR) programme and upcoming commercial activity.

  • Summary of UKAEA's approach to procurement and the supply chain

  • Dstl provides the UK with advanced space science, technology, services and advice to monitor, protect and defend our interests in and through space.

  • Dstl ensures the UK can develop and exploit new sensor technologies for our defence and security, to find and assess potential threats and give information to decision-makers.

  • A short guide to understanding and valuing data, from defining the different types of data to dealing with bad data and bias.

  • Managing radioactive waste with geological disposal

  • A guide to some different ways of visualising data and their respective strengths and weaknesses.

  • A guide to machine learning techniques for limited data problems, including approaches for small amounts of data and for large amounts of unlabelled data.

  • A simple guide and framework for thinking about artificial intelligence (AI) and autonomy from a systems perspective.

  • Supporting individuals and organisations to create and run pilot projects which take science to diverse audiences.