Why you need to collaborate

Collaborating, formally or otherwise, is a huge component of your future (and current) success – even if you’re in the early stages of your career as a graduate student or postdoc.

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Why? It’s how science works today – even in academia. You can’t do it all on your own — you need to work with others who have expertise in different areas to identify the right research questions, to ensure that your experiments answer the questions properly and that your data are robust, to fully interpret results and understand their broader implications and ramifications (as well as potential commercial application in some cases).

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Seeking out stronger science: An incomplete, non-systematic list of resources

Our reporter Monya Baker runs through some of the statistical tools she found when writing her latest story.

As I reported in a Nature feature published this week, I found more online courses that were being developed than were actually in place. Resources to help scientists do more robust research are set to expand quickly. For example, the National Institute of General Medical Sciences has a competitive program that awards funds to institutions to enhance graduate student training; of 15 such supplements awarded in 2015, a dozen involved data analysis, statistics, or experimental rigor. You can find more here, and that is only a fraction of what is available. Some courses are still being developed and piloted to select students; others are being offered only to those in a particular department or training grant. If you find one that interests you, it can’t hurt to ask.

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Counting all the ways connections matter

New research shows that the size of a faculty member’s network predicts productivity, promotion, and probability of winning an NIH R01 grant.

Guest contributor Viviane Callier

Connections matter – in terms of productivity, in terms of obtaining grants, in terms of promotion and advancement, and in terms of retention in academic positions, a new Harvard-based study shows. Women and underrepresented minorities (URMs) have a smaller “reach” – a measure of second-order connections – and the discrepancy between the reach of women & URMs and that of white men is greatest at the junior faculty level. This discrepancy may account for differences in productivity, promotion, and retention of women and URMs in academia.

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