Track: Optics
Undergrad: University of Oregon, Eugene, OR - Physics
Internship: Northrop Grumman
Current Job Title: Optical Engineer at Northrop Grumman

The Master’s Industrial Internship Program prepared me for my career in a few subtle, important ways that a standard STEM master’s degree would not. Three ways that strike me in particular are the professional development component, the tasks that ‘taught’ resourcefulness, and the ability to choose from any tool to do a certain task at hand, but that tool may not be the best one for the job.

Professional development is obviously important moving forward in an industry setting, and the master's program had an added focus on learning how to write resumes, revise resumes, bring charisma to an interview, and how in the world you’re actually supposed to network at a ‘networking event.’ I have used all of these tools since graduation and feel very well equipped in the professional world compared to my peers.

Teaching resourcefulness is never something you’d see in a list of course offerings, but it is obviously incredibly important in the corporate world, where budgets and schedule rule the bottom line. On a regular basis during the this program, we were given ambiguous tasks with short deadlines. Being able to find the right line of code, or the correct operations manual online often make or break my current daily productivity. These lab assignments helped me get comfortable navigating the unknown.

Finally, the option to use whatever analysis tool I wanted was a helpful, but painful one for me. Our lab assignments often involved data post processing or plotting, and we were allowed to use whichever tool we felt most comfortable with to do this. Coming straight out of a pure physics undergrad, I loved Mathematica and chose to do most of my work in it. This was not the correct choice, and I regularly struggled to do fairly simple tasks (since Mathematica is not optimized for this kind of data post processing). Now that I work in industry, I typically use Excel or Matlab for data post-processing, but also have learned to ask myself, ‘is this the right tool to use for this particular task?’

I loved this program, I love my job, and would highly recommend it to others who may be interested!