Personal Statement Flashcards
You say you are interested in the opportunity based on 3 core factors - what are they?
The prospect of influencing policy crucial to the IS.
The role’s agile nature and multidisciplinary environment.
Employing a range of innovative analytical techniques.
You mentioned the role is crucial to the IS - name all 4:
Artificial intelligence and data,
Ageing society,
Clean growth,
Future of mobility.
Summarise the AI and Data GC:
AI and ML are already transforming the global economy.
This challenge looks to embed AI and ML in the UK economy and set us up as a world leader in the field.
Summarise the Ageing Society GC:
Ageing populations are an issue across the world.
This challenge focuses on the demand for technology, products, and services to fit specific needs.
This is to create an economy that works for everyone.
Summarise the Clean Growth GC:
Clean Growth feeds directly into the Net Zero 2050 challenge.
The UK’s clean economy could grow at 4x the rate of GDP. New industries will be created and transformed under this umbrella.
We’re obligated to push for this in terms of ethical and economic reasons.
Summarise the Future of Mobility GC:
Future mobility covers all sorts.
How the UK’s road and rail network could drastically reduce CO2 emissions and other pollutants.
The implementation of autonomous vehicles through AI, IoT, and other systems fall under this umbrella.
Summarise the Industrial Strategy:
A long-term plan for boosting the productivity of the UK economy through the employment of the 4 Grand Challenges.
You mentioned Google AlphaFold - what is it and why is it important?
An interesting and high-impact application of AI to solving protein structure modelling.
You mention working with UKRI research councils - how and when?
On multiple occasions - main two:
On the International Data Tool namely with BBSRC as they had done similar work and offered advice on what bias to lookout for and country-specific problems.
Worked with MRC to help identify key questions that would be of use to answer when helping pull together the survey questions for the IDT.
With IT team forming UKRI grant data.
You mention employing consultant skills in the past re: UKRI grant data - what did that involve?
I took over the analytical input for pulling together the data.
It required me to convey the desires of the analytical team and manage pushback. As the task was tricky I had to feed to info too and from each team while keeping the task at pace.
You mention innovative data management and analytical methods are required for large-scale data - what do you mean?
Certain work requires large volumes of data due to complex requirements.
This can’t all be stored in Excel due to data limitations.
Other methods such as SQL are required which may take more time upfront to pull together it are worth it in the long run.
