Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2022.09.26.509546

A national professional development program fills mentoring gaps for postdoctoral researchers

Sun, T.·Drane, D.·McGee, R.·Campa, H.·Goldberg, B. B.·Hokanson, S. C.
View original source ↗Export metadata ↓

Abstract

The Postdoc Academy: Succeeding as a Postdoc was designed to build postdocs skills in career transition, career planning, collaborative research, resilience, and self-reflection. This study examined self-reported changes in five skills as learners progressed through the course. Data were collected from participants who responded to both pre- and post-surveys and engaged with the course learning activities. Results from repeated measures multivariate analysis of variance revealed that all of the self-reported perceptions of skills improved significantly upon completion of the course. Hierarchical regressions revealed that underrepresented minority learners had greater gains in their development of skills in career planning, resilience, and self-reflection. Qualitative analysis of learners responses to learning activities found that postdocs perceived networking and mentor support as contributing factors to their skill advancement while tensions among multiple obligations and concerns of uncertainties were significant challenges to applying those skills.

Source connections

Explore related subjects

scientific communication and educationPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sun, T., Drane, D., McGee, R., Campa, H., Goldberg, B. B., Hokanson, S. C.. 2022-09-27. A national professional development program fills mentoring gaps for postdoctoral researchers. https://doi.org/10.1101/2022.09.26.509546

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Evaluating Large Language Models as Tools to Navigate Researchers in Rapidly Evolving Research Landscapes: A Case Study in Cancer Drug Response Prediction

Large Language Models (LLMs) have emerged as promising tools for assisting researchers in automating and accelerating the synthesis of literature reviews. However, their reliability is a significant concern due to issues like factual inaccuracies and hallucinations. The key question is whether LLMs can reliably provide comprehensive, up-to-date overviews and analyses. This study evaluates the performance of three leading LLMs (OpenAI's ChatGPT, Google's Gemini, and DeepSeek) on the complex task of generating a comprehensive survey paper on deep learning for cancer Drug Response Prediction (DRP). By testing both standard and Deep Research (DR) / Deep Think (DT) modes of LLMs with prompts of varying detail, this paper assesses key academic dimensions, including reference management, content quality, and analytical depth. Key findings reveal that while DR modes of LLMs significantly improve reliability by eliminating hallucinations, performance variations exist across models and prompts. A trade-off between reference quantity and integration quality was observed, and even the best-performing models lacked the analytical depth of human experts, often requiring extensive human supervision. The study concludes that LLMs currently serve as powerful assistive tools but still cannot replace the critical validation and synthesis provided by human researchers. Choosing the best LLM to use depends on the task in hand, while several strategies can be implemented to improve the produced output.

scientific communication and education↗
bioRxiv2024

SIMHYB 2: a software tool to explore and illustrate evolutionary forces in Population Genetics teaching and research. Application to Conservation Genetics

Practical approaches have become a standard in many scientific disciplines, including population genetics. By analyzing properly selected datasets, the students can calculate parameters and draw conclusions about genetic diversity, differentiation and evolution of populations with higher efficiency than if based exclusively on theoretical lessons. However, preparing the appropriate datasets is a hard task and a wrong selection can spoil a well-aimed practice. Here we present SO_SCPLOWIMC_SCPLOWHO_SCPLOWYBC_SCPLOW 2, a software tool specifically intended to ease the full understanding of evolutionary forces by the students and to help the teacher to prepare adequate datasets and examples for the practices. It simulates the course of a mixed population under user-defined reproductive and evolutionary conditions. Outputs can be easily adapted for downstream analysis with other popular tools as GO_SCPLOWENC_SCPLOWAO_SCPLOWLC_SCPLOWEO_SCPLOWXC_SCPLOW or SO_SCPLOWTRUCTUREC_SCPLOW. Thus, SO_SCPLOWIMC_SCPLOWHO_SCPLOWYBC_SCPLOW 2 is very suitable for project-based-learning approaches: students can produce their own datasets in different scenarios of genetic drift, migration, selective advantage, reproductive success... Additionally, SO_SCPLOWIMC_SCPLOWHO_SCPLOWYBC_SCPLOW 2 is the only simulation software available to date providing traceable pedigrees of individuals, being therefore very convenient for preparing datasets for parentage analysis, spatial genetic structure or conservation genetics study cases. Satisfactory results from its ongoing utilization in higher education and research are reported.

scientific communication and education↗
bioRxiv2024

Postdoctoral Scholar Recruitment and Hiring Practices in STEM: A Pilot Study

Despite the importance of the postdoctoral position in the training of scientists for independent research careers, few studies have addressed recruiting and hiring of postdocs. We conducted a pilot study on postdoctoral hiring in the Division of Chemistry and Chemical Engineering at the California Institute of Technology to serve as a starting point to better understand postdoctoral recruiting and hiring processes. From this survey of both postdocs and faculty, together with the available literature, the picture emerges that the postdoc hiring process is more decentralized than either faculty hiring or graduate admissions. Postdoc positions are often filled through a passive process where the initial expression of interest from a prospective postdoc is through a "cold-call" contact to a prospective advisor. Individual faculty members are often responsible for developing and implementing their own outreach and recruitment plans and deciding who to hire into a postdoc position. The overall opacity of the processes and practices by which postdocs are identified, recruited, and hired make it difficult to pinpoint where interventions could be effective to ensure equitable hiring practices. Implementation of such practices is critical to training a diverse postdoc population and subsequently of the future STEM faculty recruited from this group.

scientific communication and education↗