Associate or Senior Editor (Machine Learning and Data Science), Nature Communications Full Time

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Job Title: Associate or Senior Editor (Machine Learning and Data Science), Nature Communications

Location: Shanghai, Beijing, Nanjing or Berlin – Hybrid working model

Closing date: 19th April, 2024 (candidates will be considered as they apply)

About The Role

Nature Communications is the leading multidisciplinary Open Access journal, publishing high-quality scientific research. To help us to build on the success of this journal, we’re seeking a researcher with a background in any area of machine learning and data science, who has a critical eye, a deep understanding of their subject and interests beyond, and who can think on their feet.

The Associate/Senior Editor role at Nature Communications is ideal for researchers who love science but feel that a career at the bench isn’t enough to sate your desire to learn more about the natural world and for those who enjoy reading papers outside their chosen area of research. This role can be located in our Berlin, Shanghai, Beijing, or Nanjing office on a hybrid working model. The position is offered on a full-time, permanent basis.

The Responsibilities Include

• Handling original research papers, and working closely with other editors on all aspects of the editorial process, including manuscript selection and overseeing peer review.
• Making well-reasoned editorial decisions on submitted manuscripts in the light of expert advice.
• Determining the representation of their subject in the journal.
• Liaising extensively with editors at other journals in the Nature family and with experts in the international scientific community.
• Attending conferences and visiting research institutions.

To Be Considered For The Position, You Will Have

• A PhD (or equivalent) in physics or mathematics or computer science. This could include, but is not limited to machine learning, data science, algorithms, statistical physics, thermodynamics etc.
• Some postdoctoral research experience is preferred but not essential. A thorough understanding of the fundamentals of the subject is essential.
• A passion for science and a thirst to learn more. You must be able to demonstrate the breadth of your interest in scientific research, both within and beyond your speciality and across the wider field of statistics and machine learning.
• Excellent communication and interpersonal skills and be fluent in English (written and spoken).
• The ability to read and assess the novelty, context and implications of research submitted to the journal from different areas of this discipline.
• Be eager to travel and meet scientists worldwide, learn more about them and their research, and help them learn more about us and what we are looking for in the papers we seek to publish.
• Editorial experience is not required, although applicants with significant editorial experience are encouraged to apply and will potentially be considered for Senior Editor positions.

To apply: Applicants should include a CV, a cover letter explaining their interest in the post and their preferred office of employment, and a separate concise (300-400 words) discussion of recent scientific developments in any area related to machine learning or data science that they found particularly exciting, stating why.

Springer Nature is a Disability Confident Committed Employer and we encourage applications from candidates with disabilities. If you consider yourself to have a disability or learning difficulty and wish to submit your application in an alternative format or would like to discuss reasonable adjustments during the application and interview process, please get in touch either by phone on +44 (0)207 014 4020 or by email SpringerNatureUKCareers@springernature.com so we can make any necessary arrangements.

If you have any access needs related to disability, neurodivergence or a chronic condition, please contact us so we can make all necessary accommodation.

At Springer Nature we value the diversity of our teams. We recognize the many benefits of a diverse workforce with equitable opportunities for everyone. We strive for an inclusive workplace that empowers all our colleagues to thrive. Our search for the best talent fully encompasses and embraces these values and principles. Springer Nature was awarded Diversity Team of the Year at the 2022 British Diversity Awards. Find out more about our DEI work here https://group.springernature.com/gp/group/taking-responsibility/diversity-equity-inclusion

For more information about career opportunities in Springer Nature please visit https://careers.springernature.com/