Call for Associate Editor Applications: Computation, AI and Machine Learning in London

Overview is a JCR-ranked, peer-reviewed academic journal owned by the Institute of Materials, Minerals and Mining (IOM3) and published by Sage Publishing. The journal is published eighteen times a year. IOM3 and Sage are seeking two dynamic and innovative Associate Editors for Materials Science and Technology (MST): one specialising in Functional Materials, and the other in Computation, AI, and Machine Learning in Materials Science. This is an exciting opportunity to shape the future of the journal during a period of transition, working closely with the new Editor-in-Chief, Radhakanta Rana, to define long-term strategy under a refreshed editorial structure.

As part of this forward-thinking team, the successful candidates will play a pivotal role in setting the research agenda, engaging with leading global researchers, and ensuring the journal remains at the forefront of its field. Successful applicants will be leaders at the cutting edge of their field, who are passionate about advancing knowledge and influencing the next era of materials science.

The aims & scope of the journal will shortly be updated, which will reflect the journal’s new editorial structure.

For this position (Associate Editor for Computation, AI and Machine Learning in Materials Science), the successful applicant will be able to demonstrate broad expertise in Computation, AI and Machine Learning, including though not limited to:

• Machine learning for materials design
• Microstructure classification
• Data-driven materials discovery
• Process optimisation
• Computational metallurgy

Materials Science and Technology is an international forum for the publication of refereed contributions covering fundamental and technological aspects of materials science and engineering. The journal has a particular interest in the continuum from understanding of process routes leading to the generation of microstructure, through characterisation and understanding of how microstructure is controlled and manipulated, to the control and prediction of relevant engineering properties. 'Microstructure' is shorthand for nano/micro/meso/macrostructure, provided that 'structure' is identified at the appropriate size scale. 'Properties' may be electrical, mechanical, electronic, chemical, magnetic, thermal, optical, or biochemically related. Reports of the use of modelling, informatics and related approaches to enhance understanding and predict properties must include validation against experimental results. Contributions addressing any part of the continuum in an insightful manner, whatever the material system, are invited. What is important is that an attempt is made to relate 'properties' back to effects of 'microstructure'. Materials Science and Technology is indexed in the Clarivate Science Citation Index Expanded (SCIE).

Editorial responsibilities

• Contributing to the overall vision and direction of the journal in collaboration with the Editor-in-Chief, Editors, members of the editorial board, IOM3, and Sage.
• Working with the Editor-in-Chief, Radhakanta Rana, and Editors to determine the content of each issue, including commissioning of key papers and special (guest edited) issues.
• Managing the flow of manuscripts, including reading submitted papers, managing the peer review process, making decisions about rejection, revision and acceptance, and corresponding with authors.
• Ensuring that publication processes, legal requirements (e.g. copyright), and deadlines are met.
• Working with the guest editors of special issues.
• Communicating with the members of the Editorial Board.
• Promoting the journal internationally, through high quality special issues and key papers, and through attending conferences.
• Keeping abreast of developments in the field and in academic publishing.

Essential Requirements

• A high academic degree in materials science, with a particular focus on the fields advertised.
• At least 5 years of experience in their field (as a professional or as an academic).
• International reputation in the required fields.
• Experience in research project management.
• International professional and/or academic links to scholars and practitioners in the field of computation, AI and machine learning in materials science.
• Experience of writing to a publishable standard in peer-reviewed outlets.
• A commitment to diverse scholarship.
• Ability to work under pressure and manage responsibilities.
• Good organisational abilities.
• Strong interpersonal skills.
• Ability to work independently.

Consideration will also be given to:

• Experience in editing and publishing.
• Experience of using ScholarOne Manuscripts, either as author or editor.

All enquiries and expressions of interest should be directed via email in the first instance to both: Tia Byer, Journal Relationship Manager, IOM3; Kate Hall, Senior Publishing Editor, Sage.