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The demand for skilled cybersecurity professionals continues to outpace supply, necessitating effective educational and workforce development programs. This exploratory study analyzes the influence of a scholarship and support activities on participants' career development through the theoretical frameworks of Social Cognitive Career Theory and career identity literature. Findings suggest that the Metropolitan State University Cyber Defenders Program bolstered participants' self-efficacy beliefs related to their academic and career pursuits, fostered positive outcome expectations regarding cybersecurity careers, and strengthened their career goals and engagement. The scholarship itself and peer interactions emerged as key supports. While overall results are positive, areas concerning perceptions of diversity within the field and the ease of finding employment warrant further exploration. 

Abstract Analysis of single-cell datasets generated from diverse organisms offers unprecedented opportunities to unravel fundamental evolutionary processes of conservation and diversification of cell types. However, interspecies genomic differences limit the joint analysis of cross-species datasets to homologous genes. Here we present SATURN, a deep learning method for learning universal cell embeddings that encodes genes’ biological properties using protein language models. By coupling protein embeddings from language models with RNA expression, SATURN integrates datasets profiled from different species regardless of their genomic similarity. SATURN can detect functionally related genes coexpressed across species, redefining differential expression for cross-species analysis. Applying SATURN to three species whole-organism atlases and frog and zebrafish embryogenesis datasets, we show that SATURN can effectively transfer annotations across species, even when they are evolutionarily remote. We also demonstrate that SATURN can be used to find potentially divergent gene functions between glaucoma-associated genes in humans and four other species.