Machine Learning: Science and Technology – a new open-access journal from IOP Publishing

09 Apr 2019 Simon Davies

IOP Publishing is launching Machine Learning: Science and Technology, a new fully open access, multidisciplinary journal devoted to the application and development of machine learning for the sciences.

The application of machine learning methods is rapidly emerging as a powerful tool for new scientific discovery. It is playing an increasingly important role in a diverse range of fields extending from novel materials design, quantum physics and the simulation of molecules and chemical systems, to particle physics, medical imaging, space science, natural disaster prediction and drug discovery.

Informed through close consultation with the community, Machine Learning: Science and Technology will be a high quality, fully open access journal that recognises the significant role machine learning will have for science and technology into the future. In doing so it will provide immediate and perpetual open access to all content under a CC-BY licence so that it can be accessed and shared by anyone without restriction.

The vision is to create a journal that uniquely bridges the application of machine learning techniques across a broad range of subject disciplines (including physics, materials science, chemistry, biology, medicine, earth science and space science) with new conceptual advances in machine learning methods motivated by physical insights.

Dr Tim Smith, Associate Director for Journals Product Development at IOP Publishing, said: “We are very excited about the launch of what represents another major new addition to IOP’s journals programme, and one that will build upon our long history in the physical sciences and open access.

“Our ambitions for Machine Learning: Science and Technology are high. Through the support of a prestigious Editorial Board we look forward to developing the journal’s content and functionality to serve all aspects of a field that looks certain to make a significant contribution to the discovery of new science into the future.”

Machine Learning: Science and Technology will open for submissions in 2019. Full details about the scope and Editorial Board can be found on the journal homepage.