Trainees Encouraged to Apply for RSNA Journals Editorial Board Opportunities

RadioGraphics, RSNA’s primary education journal and Radiology: Artificial Intelligence, RSNA’s journal highlighting the emerging applications of machine learning and artificial intelligence (AI) in the field of imaging, are accepting applications for trainee editorial board members.

Applicants to either board should be RSNA members. RSNA provides free membership for physicians and scientists in training.

RadioGraphics Trainee Editorial Advisory Members Board

Applications are open to serve on the RadioGraphics Trainee Editorial Advisory Members Board (RG TEAM).

During their two-year term, RG TEAM members will participate in the RadioGraphics mentored reviewer program, develop projects to promote and organize RadioGraphics content, serve as authors of trainee-focused editorials, RG fundamentals and RG tutorials, and engage in webinars and podcasts dedicated to educational content for trainees. RadioGraphics’ Associate Editor, David Ballard, MD, will direct the RG TEAM. Members will participate in regular videoconferences with Dr. Ballard and RadioGraphics Editor Designate, Christine (Cooky) Menias, MD.

Applicants should be residents or fellows, at any level of training, in diagnostic radiology, interventional radiology, radiation oncology and nuclear medicine. Medical students, graduate/post-doctoral students, international trainees and others will also be considered. RSNA aims to engage a diverse and international group with innovative ideas to deliver, bundle and curate content in new ways. Applicants must be in training in a relevant residency, fellowship, graduate degree program or postdoctoral fellowship throughout their RG TEAM term. The two-year term may extend past residency or fellowship.

Applicants should have strong critical-thinking skills, a mastery of written English and experience in scientific writing. They should also have unique talents and backgrounds, such as proficiency in using social media, networking and leadership skills, knowledge of technology and website-building and an interest in scholarly publishing.

To apply, submit:

• Two to four paragraph statement of interest, your qualifications and how this opportunity may benefit your career;
• An idea for trainee-focused promotion, content organization and trainee-authored editorials that you can help develop with the RG TEAM; and
• Your CV.

Applications are due Oct. 1, 2020. Questions should be directed to rg@rsna.org.

Radiology: Artificial Intelligence Trainee Editorial Board

Applications are open to serve on the Radiology: Artificial Intelligence Trainee Editorial Board (TEB).

During their two-year term, TEB members will learn about peer review, biostatistics, research design and journalistic ethics, while reviewing up to 12 manuscripts each year. TEB members will also participate in the standard Radiology: Artificial Intelligence review process and have the opportunity to contribute to the journal’s activities, such as the editor’s blog, social media or journal club. Radiology: Artificial Intelligence Associate Editor and TEB Program Director, Judy Wawira Gichoya, MD, and Radiology: Artificial Intelligence Editor, Charles E. Kahn Jr., MD, will direct and mentor the TEB.

Throughout their TEB term, applicants must be in training in a relevant residency, fellowship, graduate degree program or postdoctoral fellowship in one or more of these eligible medical disciplines: diagnostic radiology, interventional radiology, nuclear medicine and radiation oncology; or in one or more of these eligible scientific disciplines: medical physics, biomedical informatics, biomedical engineering or computer science. Applicants may reside and/or train outside of North America and should have strong critical-thinking skills, a background in health care and/or computer science, and solid knowledge of research design and basic biostatistics, a mastery of written English and experience in scientific writing.

To apply, submit:

• Two to four paragraphs of interest, your qualifications and how this opportunity may benefit your career;
• Your CV; and
• Copy of one publication representative of your work.

Applications are due Oct. 1, 2020. Questions should be directed to rad-ai@rsna.org.

For More Information

Access the current issue of RadioGraphics.

Access the current issue of Radiology: Artificial Intelligence.