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Abstract BackgroundEngineering curricula are built around faculty and accreditors' perceptions of what knowledge, skills, and abilities graduates will need in engineering careers. However, the people making these decisions may not be fully aware of what industry employers require for engineering graduates. Purpose/HypothesisThe purpose of this study is to determine how industry employer‐sought professional and technical skills vary among engineering disciplines and levels of education. Design/MethodUsing a large sample (n = 26,103) of mined job advertisements, we use the O*NET skills database to determine the frequencies of different professional and technical skills for biomedical, civil, chemical, electrical, environmental, and mechanical engineers with bachelor's, master's, and PhD degrees. ResultsThe most frequently sought professional skill is problem‐solving; the most frequently sought technical skills across disciplines are Microsoft Office software and computer‐aided design software. Although not the most frequently requested skills, job advertisements including the Python and MATLAB programming languages paid significantly higher salaries than those without. ConclusionsThe findings of this study have important implications for engineering program leaders and curriculum designers choosing which skills to teach students so that they are best prepared to get and excel in engineering jobs. The results also show which skills students can prioritize investing their time in so that they receive the largest financial return on their investment. 

Abstract BackgroundDespite many initiatives to improve graduate student and faculty diversity in engineering, there has been little or no change in the percentage of people from racially minoritized backgrounds in either of these groups. Purpose/HypothesisThe purpose of this paper is to counter the scarcity fallacy, in which institutions blame the “shortage” of qualified people from traditionally marginalized backgrounds for their own lack of representation, related to prospective PhD students and prospective faculty from traditionally marginalized groups. This study identifies the BS‐to‐PhD and PhD‐to‐tenure‐track‐faculty institutional pathways of Black/African American and Hispanic/Latino engineering doctorate recipients. Design/MethodUsing the US Survey of Earned Doctorates, we tracked the BS‐to‐PhD institutional pathways of 3952 Black/African American and 5732 Hispanic/Latino engineering PhD graduates. We also used the Survey of Doctorate Recipients to track the PhD‐to‐tenure‐track faculty pathways of 104 Black/African American and 211 Hispanic/Latino faculty. ResultsThe majority of Black/African American and Hispanic/Latino PhD graduates in this study did not earn their BS degrees from Top 25 institutions, but rather from Not Top 25, non‐US, and minority‐serving institutions. The results also show the relatively small proportion of PhD earners and faculty members who move into highly ranked institutions after earning a bachelor's degree from outside this set of institutions. ConclusionsThe findings of this study have important implications for graduate student and faculty recruitment by illustrating that recruitment from a narrow range of institutions (i.e., Top 25 institutions) is unlikely to result in increased diversity among racially minoritized PhDs and faculty in engineering. 

Abstract We summarize national-scale data for Ph.D. earners in engineering or computer science from 2015 to 2019 whose post-graduate school employment is known, highlighting outcomes for biological/biomedical/biosystems engineering students. We use NSF’s Survey of Earned Doctorates (SED), which has collected information from Ph.D. recipients in the USA since 1957. The data are collected at the time of degree completion and constitute a greater than 90% response rate. Compared to all engineering and computer science disciplines, biological/biomedical/biosystems engineering has a higher proportion going to 4yr/med/research institutions (52% vs. 33%) and non-profit (3.6% vs. 2.9%) and lower proportion going to industry (33% vs. 48%), government (4.3% vs. 8.4%), and is similar for non-US positions (6.1% vs. 5.7%). Compared to 2010–2014 biological/biomedical/biosystems engineering Ph.D. recipients, more 2015–2019 recipients are going to industry (25% to 33%) and fewer to 4yr/med/research institutions (59% to 52%) and governmet (5.3% to 4.3%). Across all engineering and computer science disciplines, a smaller proportion of females entered industry (43%) compared to males (49%), while a larger proportion of females entered 4yr/med/research institutions (37%) compared to males (32%). Over half of Asian doctoral recipients entered industry, as compared to 38% of Hispanic doctoral recipients. In contrast, a higher proportion of Hispanic individuals (37%) entered 4yr/med/research institutions after their doctoral programs, as compared to 31% of Asian doctoral recipients. Black doctoral recipients had the highest proportion enter positions in government (14%) and non-profit (4%) sectors. Our results are situated in the broader literature focused on postdoctoral career, training, and employment sectors and trends in STEM. We discuss implications for graduate programs, policymakers, and researchers. 

Abstract Whether doctoral students are funded primarily by fellowships, research assistantships, or teaching assistantships impacts their degree completion, time to degree, learning outcomes, and short- and long-term career outcomes. Variations in funding patterns have been studied at the broad field level but not comparing engineering sub-disciplines. We addressed two research questions: How do PhD student funding mechanisms vary across engineering sub-disciplines? And how does variation in funding mechanisms across engineering sub-disciplines map onto the larger STEM disciplinary landscape? We analyzed 103,373 engineering and computing responses to the U.S. Survey of Earned Doctorates collected between 2007 and 2016. We conducted analysis of variance with Bonferroni post hoc comparisons to examine variation in funding across sub-disciplines. Then, we conducted a k-means cluster analysis on percentage variables for fellowship, research, and teaching assistantship funding mechanism with STEM sub-discipline as the unit of analysis. A statistically significantly greater percentage of biomedical/biological engineering doctoral students were funded via a fellowship, compared to every other engineering sub-discipline. Consequently, biomedical/biological engineering had significantly lower proportions of students supported via research and teaching assistantships than nearly all other engineering sub-disciplines. We identified five clusters. The majority of engineering sub-disciplines grouped together into a cluster with high research assistantships and low teaching assistantships. Biomedical/biological engineering clustered in the high fellowships grouping with most other biological sciences but no other engineering sub-disciplines. Biomedical/biological engineering behaves much more like biological and life sciences in utilizing fellowships to fund graduate students, far more than other engineering sub-disciplines. Our study provides further evidence of the prevalence of fellowships in life sciences and how it stretches into biomedical/biological engineering. The majority of engineering sub-disciplines relied more on research assistantships to fund graduate study. The lack of uniformity provides an opportunity to diversify student experiences during their graduate programs but also necessitates an awareness to the advantages and disadvantages that different funding portfolios can bestow on students.