As a recent Ph.D. graduate, a recruiter contacted me via email just before graduation. This was surprising because I have no internship experience at Google. Several platform teams were interested in me, and I scheduled interviews ASAP.

I skipped phone interviews and proceeded directly to five on-site interviews: three coding questions, one system design question, and one personality interview. In general, you would be notified what you are expected to study.

Coding questions were within the range of my expectations. I chose Python to reduce coding time in interviews because its code is very similar to pseudocode in algorithm textbooks. What you need to do is:

• Come up with a high-level algorithm.
• Implement it.

To prepare for this, my suggestion is:

• Read an algorithm book and become familiar with strategies to solve problems (e.g., divide-and-conquer, graph algorithms, dynamic programming, etc.).
• Practice writing your high-level ideas in your own language.

It also seems important to write completely working code. Typically, you're given a simple example, and you run with it for debugging. It would also be helpful to practice running your own implementation with small examples, which I didn't do before the interviews.

I was assigned an unfamiliar field for the system design questions, so I barely answered what the interviewers expected. Still, I was told it would be fine because they understood it wasn't my field. In the last interview, I was asked about my experience with collaborations, something graduate students often lack.

I have just finished the interviews and haven't received the results back.

Find the occurrence of a given item in a sorted list.