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The Postdoc Appreciation Week (PAW) has been celebrated in the USA and UK for years to bring postdocs into the limelight. We are strongly convinced that postdocs in Germany also deserve more attention, visibility and support given their key role in the German academic system – and their difficult working conditions and career perspectives coupled with an often very one-dimensional evaluation culture. We composed this toolkit for all those who want to contribute to the PAW. Be it as a professor or teamleader, a postdoc network or a postdoc service or other stakeholders who want to thank postdocs for their great work and who want to support them! We would like to thank our colleagues from the National Postdoc Association in the U.S. who inspired us to establish a Postdoc Appreciation Week in Germany and provided us with valuable material in the form of their “National Postdoc Appreciation Week Toolkit”. We have added our own ideas and best-practice examples from the first German Postdoc Appreciation Week 2022 and 2023. We also thank the Max Planck Institute of Biochemistry (MPIB) who created the PAW logo. Please spread the word and feel free to share our materials with your colleagues, teamleaders, social media managers, and everyone else involved in supporting postdocs in Germany.
Toolkit, Appreciation, Postdoc
Toolkit, Appreciation, Postdoc
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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