CSE 2013: Navigating the Paths to a Career in CSE

June 3, 2013


Organizers of the Student Careers Panel (from left): Luke Olson, University of Illinois at Urbana–Champaign, Karen Willcox, MIT, and Gianluigi Rozza (chair), SISSA, International School for Advanced Studies, Trieste, Italy. Photo by Susan Whitehouse.
Andrew D. Davis

The interdisciplinary nature of many academic questions and the wide array of applications can make choosing a career path in computational science and engineering difficult. Theoretical tools are constantly being developed and must be implemented and used in the seemingly endless array of applications. This year's SIAM Conference on Computational Science and Engineering scheduled a panel discussion (sponsored by The MathWorks and IBM) to help undergraduate and graduate students navigate this diverse field and choose a career path. The four panelists, Kirk E. Jordan, Tamara G. Kolda, Jill Reese, and Gilbert Strang, served as representatives of careers in academia, industry, and national labs. The discussion focused on the progression of typical careers in each of the three areas, the challenges faced in switching career tracks, and ways to supplement graduate school with internships.

Many in the audience were interested in pursuing tenure-track jobs at research universities. Some had questions about how to apply for such jobs. Specifically, one student wanted to know the departments to which computational science and engineering students should apply. As for many in the audience, this student's research was a blend of mathematics, computer science, and an application. Because many universities do not have computational science departments, it was unclear whether the student should apply for a professorship in mathematics, computer science, or an engineering discipline. The panel's suggestion: Rather than pick a single department, look for openings in any department that has a computational component, the logic being that an applicant's current research and research interests will determine whether s/he matches what the department wants. The interdisciplinary nature of computational applications means that students with similar educational backgrounds can pursue academic careers in very different fields.

Industrial companies often hire students with degrees in CSE. Students in the audience who were interested in pursuing research-based careers asked how research at a company was different from research at a university. One student, in particular, wanted to know how difficult it would be to transition from industry to academia. The panel pointed to the importance of journal publications for success in academia, whereas the ability to publish in an industrial job depends on the job and the company. Students pursuing industrial careers, but with an interest in moving to academia later in their careers, were encouraged to look for jobs that would allow them to publish. Two of the panelists had had graduate students work for them, either as interns or in collaboration with a professor; they suggested that pursuing jobs with such opportunities would facilitate a switch from industry to academia.

Labs account for many of the career options for students graduating with degrees in CSE. One student asked the panel to compare being a researcher at a lab to being a professor. A major difference identified by the panel was the effect of not having students on the research group structure. At universities, professors use their advisees to create a research direction for the group. At labs, which do not have students, the panel described a system based more on peer-to-peer collaboration. Often, each person involved in a lab project is an expert in a different field, as opposed to universities, where the students in a group are studying similar subjects.

Students were also interested in learning about more short-term career options. A few students had completed or been offered internships. Should graduate students take internships? Or should they focus more on their dissertations? The panel began by pointing out that internships can often be designed to relate to students' research, especially if their advisers have engaged in industrial collaborations. Two panelists had supervised graduate interns, and one had had internships as a graduate student. They argued that such experiences, by exposing students to jobs outside academia, might help them decide which of the three typical career paths best suits them. Students then asked how to approach their advisers about accepting internships. The panel encouraged a direct approach; advisers, they pointed out, often have collaborative projects that provide internship opportunities. Additionally, advisers can make sure that an internship does not interfere with the student's graduation time line.

Overall, students wanted to know what they could do to maximize their opportunities for career advancement. Among other concerns were how to choose a PhD program and how long a potential employer would expect a PhD to take. The panelists conveyed diverse points of view on how students could become successful computational scientists. In the end, their advice was to remain passionate and curious and to pursue any appealing opportunity that arises.

Andrew D. Davis is a PhD student at MIT, working under the supervision of Youssef Marzouk and Patrick Heimbach. His dissertation research is in large-scale parameter inference for prediction.



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