DA CDT Interview Guidance for Applicants

Interviews typically take up to one hour and you will present a video (please review the Video Requirements for CDT Interview guidance note) and be asked questions that will enable the academics supervisors to find out more about you, your research interest and your skill set.

Their focus is on assessing four aspects of your experience: it is important for the assessment to focus on what you have done, not what you might plan to do (since anyone can plan anything, but only you have done the combinations of things that you have done). 

The purpose of the PhD is to train you such that you will have all the skills and experience a graduate needs at the end of the PhD: while we are obviously keen to understand where your current strengths are, there's no point applying if you have all the skills already!

The questions will therefore focus on collating the evidence that enables the supervisors to quantify your suitability for undertaking the PhD. The aspects of your experience that the supervisors need to assess and questions that exemplify the questions you might be asked in the context of each of the four aspects of your experience are as follows (you wouldn't be asked all of these, but we've deliberately provided a longer list than we might do to give you as good an idea as we can of what sort of things might be asked):

  1. Your background in "Data Science" (which we assume goes beyond Computer Science and includes what Mathematicians call statistics, Engineers call signal processing and scientists call quantitative methods):

    • What experience do you have of clustering, classification and regression?

    • Can you explain what you did in your most recent degree that is relevant to Data Science?

    • What's the smallest dataset you have analysed?

    • What's the most interesting research paper that you have you read?

  2. Your background in "Future Computing Systems" (which we assume includes programming, but might also include use of HPC, Big Data middleware (MPI, Hadoop, Spark etc)) 

    • What programming languages have you used?

    • What experience do you have of using HPC?

    • How many lines of code have you written?

    • How do you ensure that the code base you have written is easy for others to follow

  3. Your experience of working with people outside academia

    • How did you engage with the people that would use the output of your most recent project?

    • What did you feel were the differences between the people you encountered in your degree and the people you encountered when you were working in the holidays/between school terms?

    • What did you learn from your interaction with people working outside academia?

  4. Your alignment with the specifics of the project and the CDT more general

    • What makes the vision for the DA CDT (link to programme overview) appeal to you?

    • What makes the cohort-based training model that the DA CDT adopts appeal to you?

    • Why do you want to do this PhD?

    • What evidence do you have that you are a quick learner who is likely to flourish in the CDT and beyond?