This work uses the same methodology as work from previous years to study where Computer Science departments are choosing to invest faculty positions by examining data obtained from advertised faculty searches for the current hiring season. While the number of and areas for faculty searches does not necessarily translate into the same for faculty hires, we believe that they provide insight into current and future needs within the discipline.
We analyzed ads from 406 institutions seeking to fill hundreds of tenure-track faculty positions in Computer Science. There is a 17% one-year (and 52% two-year and 82% three-year) increase in the number of institutions searching for tenure-track faculty in Computer Science and a 21% one-year (and 64% two-year and 107% three-year) increase in the number of positions being searched for. The number of institutions searching and positions seeking to be filled has increased the most for BS institutions.
In terms of specific areas, we found that the clustered areas of Security, Data Science and AI/Data Mining/Machine Learning are the areas of greatest investment. Aggregating the Data Science, AI/DM/ML and Databases clusters results in close to one-third of all hires sought in these data-oriented areas. We again found that 30-60% of all hires are for areas that are, or may be, interdisciplinary in nature.
Differences are also seen when analyzing results based on the type of institution. Positions related to Security have the highest percentages for top-100 PhD, MS and BS institutions. Data Science is of most interest for other PhD institutions. 35% of positions for PhD institutions are in data-oriented areas. Finally, the abundance of potentially interdisciplinary areas is most pronounced for PhD institutions with 32-65% of all positions devoted to these areas.
The full report containing a description of the methodology and the complete results is available at