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      Ten Simple Rules for a successful remote postdoc

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          Author summary

          Postdocs are a critical transition for early-career researchers. This transient period, between finishing a PhD and finding a permanent position, is when early-career researchers develop independent research programs and establish collaborative relationships that can make a successful career. Traditionally, postdocs physically relocate—sometimes multiple times—for these short-term appointments, which creates challenges that can disproportionately affect members of traditionally underrepresented groups in science, technology, engineering, and mathematics (STEM). However, many research activities involving analytical and quantitative work do not require a physical presence in a lab and can be accomplished remotely. Other fields have embraced remote work, yet many academics have been hesitant to hire remote postdocs. In this article, we present advice to both principal investigators (PIs) and postdocs for successfully navigating a remote position. Using the combined experience of the authors (as either remote postdocs or employers of remote postdocs), we provide a road map to overcome the real (and perceived) obstacles associated with remote work. With planning, communication, and creativity, remote postdocs can be a fully functioning and productive member of a research lab. Further, our rules can be useful for research labs generally and can help foster a more flexible and inclusive environment.

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          Most cited references11

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          How Gender and Race Stereotypes Impact the Advancement of Scholars in STEM: Professors’ Biased Evaluations of Physics and Biology Post-Doctoral Candidates

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            When Two Bodies Are (Not) a Problem: Gender and Relationship Status Discrimination in Academic Hiring

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                7 May 2020
                May 2020
                : 16
                : 5
                : e1007809
                Affiliations
                [1 ] Education Department, Cary Institute for Ecosystem Studies, Millbrook, New York, United States of America
                [2 ] Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, Connecticut, United States of America
                [3 ] Climate Change Institute, University of Maine, Orono, Maine, United States of America
                [4 ] David H. Smith Conservation Research Program, Society for Conservation Biology, Washington, DC, United States of America
                [5 ] Department of Ecology and Evolutionary Biology, University of Toronto, St. George, Ontario, Canada
                [6 ] Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, United States of America
                [7 ] Informatics Institute, University of Florida, Gainesville, Florida, United States of America
                [8 ] Biodiversity Institute, University of Florida, Gainesville, Florida, United States of America
                [9 ] School of Biology and Ecology, University of Maine, Orono, Maine, United States of America
                [10 ] Department of Ecology, Evolution, and Marine Biology, University of California Santa Barbara, Santa Barbara, California, United States of America
                [11 ] Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, British Columbia, Canada
                Carnegie Mellon University, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                ‡ These authors also contributed equally to this work

                Author information
                http://orcid.org/0000-0002-8375-2501
                http://orcid.org/0000-0002-2775-5628
                http://orcid.org/0000-0002-1802-7354
                http://orcid.org/0000-0002-6026-8530
                http://orcid.org/0000-0003-0003-6620
                http://orcid.org/0000-0002-0111-3619
                http://orcid.org/0000-0001-5322-2617
                Article
                PCOMPBIOL-D-19-01648
                10.1371/journal.pcbi.1007809
                7205202
                32379759
                136fca45-04c0-4c0d-a62c-14368a5fb2eb
                © 2020 Burgio et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Page count
                Figures: 2, Tables: 0, Pages: 9
                Funding
                This work was partially supported by the Gordon and Betty Moore Foundation’s DataDriven Discovery Initiative through grant GBMF4563 to EPW ( https://www.moore.org/programs/science). KRB was supported by National Science Foundation NRT- IGE grant #1545458 (awarded to M. Rubega) ( https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505473). CMM, SBB, KEI, and AKT are supported by the David H. Smith Conservation Research Fellowship, funded by the Cedar Tree Foundation and administered by the Society for Conservation Biology ( http://cedartreefound.org/smith-fellows-program). AKT is also supported by a Mitacs Accelerate Fellowship (IT12751) co-sponsored by the Pacific Salmon Foundation and Genome British Columbia ( https://www.mitacs.ca/en/programs/accelerate/fellowship). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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