Overview
The Bank for International Settlements (BIS) is offering PhD fellowships aimed at individuals eager to engage in research related to applied economics and central banking. This initiative presents a unique opportunity for PhD students to apply their skills in machine learning to significant economic challenges.
Background & Relevance
The intersection of machine learning and economics is a rapidly evolving field. With the increasing complexity of economic data, traditional methods often fall short in analyzing non-standard time-series data. The application of advanced machine learning techniques, particularly transformer models, can provide deeper insights and more accurate predictions in economic contexts. This relevance is underscored by the growing need for innovative approaches in central banking and economic research.
Key Details
- Institution: Bank for International Settlements (BIS)
- Research Focus: Applied economics and central banking
- Model Applications: Machine learning, particularly transformer models for time-series data
- Application Link: BIS Careers
Eligibility & Participation
These fellowships are targeted at PhD students from computer science departments who have a keen interest in applying machine learning techniques to economic data. Candidates should be motivated and ready to contribute to impactful research in this domain.
Submission or Application Guidelines
Interested candidates are encouraged to reach out directly to Fernando Perez-Cruz via email at fernando.perez-cruz@bis.org or through LinkedIn to discuss potential project submissions and further details regarding the application process.
Additional Context / Real-World Relevance
The integration of machine learning into economics is not just a theoretical exercise; it has real-world implications for policy-making and financial stability. As central banks increasingly rely on data-driven insights, the ability to analyze complex datasets using advanced machine learning techniques becomes essential. This fellowship aligns with the broader trend of enhancing economic research through innovative technological applications.
Conclusion
The BIS PhD fellowships represent a valuable opportunity for aspiring researchers to delve into the application of machine learning in economics. Interested individuals are encouraged to explore this opportunity, submit their projects, and contribute to the evolving landscape of economic research.
Category: PhD & Postdoc Positions
Tags: machine learning, applied economics, central banking, transformer models, time-series data, novel machine learning models, BIS, computer science
