Doctoral Researcher / Väitöskirjatutkija (Deep Learning for High-Frequency Financial Data Modeling)

Doctoral Researcher / Väitöskirjatutkija (Deep Learning for High-Frequency Financial Data Modeling)

Tampere University and Tampere University of Applied Sciences create a unique environment for multidisciplinary, inspirational and high-impact research and education. Our university community has its competitive edges in technology, health and society. www.tuni.fi/en.

We are looking for a Doctoral Researcher to work on deep learning methodologies for high-frequency financial data modeling. The selected applicant will be member of the Computational Intelligence group led by Professor Alexandros Iosifidis, and closely collaborate with the Financial Data Science group led by Professor Juho Kanniainen, at the Unit of Computing Sciences of Tampere University. The position is full-time and will be filled as soon as possible for a fixed-term period of four years. The workplace is located at Hervanta Campus of Tampere University, Finland.

JOB DESCRIPTION

The Doctoral Researcher will conduct research on designing, implementing, and proposing new Machine/Deep Learning methods and models for Financial Markets. Topics of interest include generative models for financial data synthesis and/or forecasting, trustworthy financial data predictions, world models for financial markets, system-II predictive models, and multi-model multi-asset routing mechanisms for financial predictions.

The project combines real-world financial data analysis with hands-on design and development of Machine Learning models that push the state-of-the-art, with room to shape the direction of research based on the researcher's interests. Writing high-level scientific publications is an essential part of the research.

In addition to the research towards the doctoral dissertation, the duties of the researcher may include some teaching tasks (5-10%) or other small faculty tasks that support the studies.