UCL Computer Science invites applications for a fully funded 4-year Ph.D. studentship (full-time) affiliated with the Financial Computing and Analytics group starting October 2022 under the supervision of Dr. Silvia Bartolucci.
About the project
The last decade has witnessed the rapid emergence and uptake of digital technologies and platforms affecting all business sectors. In finance, challenger banks and tech startups, digital assets, and novel decentralised payment networks are new competitors of the classic stakeholders (banks, hedge funds) and assets.
In terms of the broad so-called fintech ecosystem, the research will focus on understanding its evolutionary dynamics, focusing on how endogenous and/or exogenous factors (e.g., region-specific financial regulations) may affect or foster its growth (e.g., in terms of market share, adoption, stability).
Concerning decentralised platforms offering financial services (e.g., peer-to-peer lending, borrowing, and trading), research questions relate – among other aspects—to (i) how to build resilient and future-proof incentive systems to ensure adoption and active participation of peers and (ii) understanding the dynamics of platforms’ competition, technological spillovers, and the impact on their valuation.
A growing body of literature across multiple disciplines – such as Economics, Physics and Computer Science – has tackled these issues from different angles. The goal of this project is to analyse the long-run economic, policy implications, and impact of these new digital technologies leveraging complex systems (i.e., network and agent-based modelling calibrated on real data) and data analytics tools. The candidate will for instance design, simulate and – when possible – solve analytically agent-based models of interacting peers considering different incentive and cost structures, reproducing different types of decentralised systems to test the emergent dynamics of adoption, as well as possible vulnerabilities to different types of attacks. Part of the research will entail gathering, analysing, and interpreting data obtained from decentralised platforms (e.g., transactions and users’ participation) as well as data concerning the broader fintech and innovation ecosystem (e.g., fintech startups and patent data).
Several research directions may stem from this project depending on the specific interests and skills of the applicant. This project will benefit from continuous feedback and interactions with industry partners, e.g., fintech startups and data providers currently collaborating with the Financial Computing and Analytics group and the wider UCL Computer Science community.
Relevant skills and experience are listed below:
· A BSc or MSc degree in Physics, Mathematics, Computer Science or related fields
· Strong interest in interdisciplinary research and complex systems approaches (e.g., network theory, stochastic processes)
· Experience with numerical simulations and scientific computing
· Experience with data scraping, analysis and visualization in Python/R
· Strong mathematical background
· Good communication skills, especially in written English
· Ability to think creatively and work both independently and collaboratively within a team
How to apply
A complete formal application including CV and research statement must be submitted by August 12th, 2022 via UCL’s application system https://www.ucl.ac.uk/prospective-students/graduate/research-degrees/computer-science-4-year-programme-mphil-phd.
Please quote the title of the project and the leading PhD supervisor [Dr. Silvia Bartolucci]. The research statement should include: (i) research experience (if any) and relevant skills for the project, (ii) potential contributions to the project and your main areas of interest, (iii) name of at least two academic referees. Please also link your Github/code repository and dissertation if available.
Candidates who have alternative funding methods (e.g., self-funded) or that wish to start later are also encouraged to apply.
Interested candidates can informally contact Dr. Silvia Bartolucci ([Email Address Removed]) before applying, sending a CV and a short paragraph about their research interests.