The project will first combine data science and statistical methods to analyse unstructured data from patents, publications and new open sources of “big data” (e.g. GitHub, arXiv, Crunchbase, University websites and Burning Glass Technologies) to measure sectoral and regional exposure to AI and Robots (AI/R). Second, the project will assess the job and wage multiplier effect of AI/R in local labour markets (https://ideas.repec.org/p/sru/ssewps/2018-08.html).
The unique combination of the supervision arrangement will expose the PhD student to academic rigour and top level policy engagement on a crucial and timely topic. This will open a wide range of career opportunities in academia, policy making, the third sector and consultancy. The student will be jointly supervised by expert innovation economists and data scientists at Sussex and Nesta
The successful PhD candidate will be expected to start in September 2019.
The student will have the opportunity to attend advanced courses in Data science and other quantitative methods, Science and Technology Policy, and Economics from the University of Sussex and partners across SeNSS. The student will also become part of the innovation mapping community at Nesta, including experienced data developers, data scientists, visualisation designers and policy analysis who will provide advice, support and mentoring through the project.
* This studentship may be taken as either a 1+3 year award (a one-year MSc followed by a three-year PhD), a +3 award (a three-year PhD), or a +4 award (a four year PhD)
* It may be taken full-time or part-time
* The studentship award covers your university fees, and provides you with a stipend of £14,777 per year. You will also be able to apply for small amounts of additional funding via the SeNSS Research Training Support Grant.
Applicants essential and/or desirable attributes/skills
* Master in Economics, Data Science, or related disciplines. We welcome strong applicants with interdisciplinary backgrounds and quantitative skills
* Willingness to attend advanced training in data science
* Fluent in oral and written English
* Programming languages and data analysis packages (e.g. SQL, Python, R, STATA)
* Text mining
* Experience with patent and unstructured data
How to apply for this studentship
In order to be considered for this SeNSS studentship, you must first apply for a place to study at the University of Sussex, noting that you are applying for the collaborative studentship. Please go to University of Sussex: apply for a PhD for information on how to make your application and apply to a Science and Technology Policy Studies PhD.
You will then need to make a separate application to SeNSS for this collaborative studentship. Please read the SeNSS Collaborative Studentship Application Guidance Notes before completing our online application form. The Guidance Notes are available at the bottom of the following webpage: Applying for a SeNSS collaborative studentship
The deadline applying to the University of Sussex for a place is 23:59 GMT on 20 January 2019. No extensions to this deadline will be permitted.
It is open to Home/EU students who meet the UK Research Council residential eligibility criteria. Further details about this, and academic eligibility requirements, can be found on the following webpage: https://www.sussex.ac.uk/study/phd/doctoral/funding-support/south-east-network-social-sciences
For further enquiries
For enquiries related to the studentship topic, please email Tommaso Ciarli (email@example.com)
Brighton , United Kingdom