The process began with an hour-long interview with a researcher, covering topics such as mathematics, machine learning, deep learning, and computer science.

Following this, a virtual onsite included a presentation and several technical interviews. These interviews focused on different areas:

• Mathematics
• Machine learning
• Applied machine learning
• Coding
• Behavioural

The interviewers were good and made me feel comfortable.

After a month, they responded, stating they believed I wasn't a good fit.

Machine Learning:

• MAP and predictive distribution
• How does KNN work and its trade-offs
• Some questions about CNN

Mathematics:

• Linear algebra (finding the eigenvalues of a 2x2 matrix)
• Calculus (computing the gradient of some function and integrating log(x^3))
• Limit of exponent over factorial series, etc.

Coding:

• Some questions on data structures and a simple coding exercise.

Behavioural:

• Lots of questions about my experience and ambitions, plus some mental exercises.