New study of computer scientists says that when it comes to research output, where Ph.D.s get hired matters more than where they trained.

The data in this report summarises the responses gathered from 365 principle investigators of academic laboratories, who started their independent positions in the UK within the last 6 years up to 2018. We find that too many new investigators express frustration and poor optimism for the future. These data also reveal, that many of these individuals lack the support required to make a successful transition to independence and that simple measures could be put in place by both funders and universities in order to better support these early career researchers. We use these data to make both recommendations of good practice and for changes to policies that would make significant improvements to those currently finding independence challenging. We find that some new investigators face significant obstacles when building momentum and hiring a research team. In particular, access to PhD students. We also find some important areas such as starting salaries where significant gender differences persist, which cannot be explained by seniority. Our data also underlines the importance of support networks, within and outside the department, and the positive influence of good mentorship through this difficult career stage.

Gender and Precarious Research Careers aims to advance the debate on the process of precarisation in higher education and its gendered effects, and springs from a three-year research project across institutions in seven European countries. Examining gender asymmetries in academic and research organisations, this insightful volume focuses particularly on early careers. It centres both on STEM disciplines (Science, Technology, Engineering and Mathematics) and SSH (Social Science and Humanities) fields.

Universities are at long last undertaking efforts to collect and disseminate information about student career outcomes, after decades of calls to action. Organizations such as Rescuing Biomedical Research and Future of Research brought this issue to the forefront of graduate education, and the second Future of Biomedical Graduate and Postdoctoral Training conference (FOBGAPT2) featured the collection of career outcomes data in its final recommendations, published in this journal (Hitchcock et al., 2017). More recently, 26 institutions assembled as the Coalition for Next Generation Life Science, committing to ongoing collection and dissemination of career data for both graduate and postdoc alumni. A few individual institutions have shared snapshots of the data in peer-reviewed publications (Mathur et al., 2018; Silva, des Jarlais, Lindstaedt, Rotman, Watkins, 2016) and on websites. As more and more institutions take up this call to action, they will now be looking for tools, protocols, and best practices for ongoing career outcomes data collection, management, and dissemination. Here, we describe UCSF's experiences in conducting a retrospective study, and in institutionalizing a methodology for annual data collection and dissemination. We describe and share all tools we have developed, and we provide calculations of the time and resources required to accomplish both retrospective studies and annual updates. We also include broader recommendations for implementation at your own institutions, increasing the feasibility of this endeavor.

Mentorship in academia facilitates personal growth through pairing trainees with mentors who can share insight and expertise.Expertise can be purely academic, on work‐life balance, personal branding and networking, or general career advice. Mentoring has been shown to be beneficial for mentees, both in terms of objective research productivity and subjective outcomes. Several institutions/organizations have formal in‐person mentoring programs that pair early‐ to mid‐career researchers with mentors who are not their direct supervisors. With global integration in science, however, geographical proximity between mentors and mentees is relevant to a lesser degree.

Women researchers are underrepresented in almost all research fields. There are disciplinary differences in the phase in which they tend to quit their academic career: in the natural and technical sciences (STEM), it is in the postdoctoral phase, whereas in the social sciences and humanities (SSH) it is during the doctoral phase.

The potential costs for early-career researchers in adopting practices to improve reproducibility as well as ways in which they can nontheless achieve their career goals.

In the 21st Century, research is increasingly data- and computation-driven. Researchers, funders, and the larger community today emphasize the traits of openness and reproducibility. In March 2017, 13 mostly early-career research leaders who are building their careers around these traits came together with ten university leaders (presidents, vice presidents, and vice provosts), representatives from four funding agencies, and eleven organizers and other stakeholders in an NIH- and NSF-funded one-day, invitation-only workshop titled “Imagining Tomorrow’s University.” Workshop attendees were charged with launching a new dialog around open research – the current status, opportunities for advancement, and challenges that limit sharing.

The workshop examined how the internet-enabled research world has changed, and how universities need to change to adapt commensurately, aiming to understand how universities can and should make themselves competitive and attract the best students, staff, and faculty in this new world. During the workshop, the participants re-imagined scholarship, education, and institutions for an open, networked era, to uncover new opportunities for universities to create value and serve society. They expressed the results of these deliberations as a set of 22 principles of tomorrow's university across six areas: credit and attribution, communities, outreach and engagement, education, preservation and reproducibility, and technologies.