Post-doctoral Fellowship in Computational Finance

A Post-Doctoral fellowship position is available at the Technological Institute of Aeronautics (ITA) in Brazil. The researcher will be involved in the project “Employing computational intelligence techniques and big data analytics in a multi-agent system experiment of finance”, a collaboration between ITA and the University of Essex, UK. This project and the PD fellowship are funded by FAPESP (São Paulo Research Foundation,

This research intends to employ different computational intelligence techniques (reinforcement learning, genetic algorithm and fuzzy logic) and big data analytics in a multi-agent system experiment (agent-based model simulation of a double auction market) of finance. This research has the following objectives: 1) to investigate the ability of reinforcement learning to model the agent’s learning and evolution process in the financial markets, 2) to study the use of multi-criteria performance indexes in order to model the agent’s learning process, and 3) to analyse the consequence of this agent’s behaviour to the financial markets as a whole.

Applications should be submitted only by e-mail until May 2, 2017. Those interested should send letter of interest, curriculum vitae and at least one letter of recommendation to the project’s Principal Investigator, Dr. Cairo Nascimento ([email protected]).

The monthly stipend of the FAPESP post-doctoral fellowship is R$ 6.819,30 (approximately US$ 2.200,00), and the duration of the fellowship is 18 months.

Candidates must have obtained their PhD degree in Computational Finance or in a similar field of study less than seven years before the beginning of the PD fellowship, and have expertise in computational finance, artificial intelligence, data analytics and multi-agent systems. Fluency in English and ability to work within interdisciplinary teams are also mandatory. Previous experience in the financial market micro-structure is desired but not mandatory.

See for additional candidate’s requirements and obligations.

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