{"id":3847995,"date":"2026-08-24T16:00:00","date_gmt":"2026-08-24T13:00:00","guid":{"rendered":"https:\/\/laura.fi\/vacancies\/company\/doctoral-researcher-vaitoskirjatutkija-deep-learning-for-high-frequency-financial-data-modeling\/doctoral-researcher-vaitoskirjatutkija-deep-learning-for-high-frequency-financial-data-modeling\/"},"modified":"2026-08-24T17:00:06","modified_gmt":"2026-08-24T14:00:06","slug":"3847995","status":"publish","type":"job_listing","link":"https:\/\/laura.fi\/en\/vacancies\/tampereen-yliopisto\/doctoral-researcher-vaitoskirjatutkija-deep-learning-for-high-frequency-financial-data-modeling\/3847995\/","title":{"rendered":"Doctoral Researcher \/ V\u00e4it\u00f6skirjatutkija (Deep Learning for High-Frequency Financial Data Modeling)"},"content":{"rendered":"

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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<\/a>.\u00a0<\/em><\/p>\n

We are looking for a Doctoral Researcher to work on deep learning methodologies for high-frequency financial data modeling.\u00a0<\/strong>The selected applicant will be member of the Computational Intelligence group led by Professor Alexandros Iosifidis<\/a>, and closely collaborate with the Financial Data Science group led by Professor Juho Kanniainen<\/a>, 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.<\/p>\n

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JOB DESCRIPTION<\/strong><\/p>\n

The\u00a0Doctoral Researcher<\/strong> 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<\/strong>.\u00a0<\/p>\n

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\u2019s interests. Writing high-level scientific publications is an essential part of the research.\u00a0<\/p>\n

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.<\/p>\n

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REQUIREMENTS<\/strong><\/p>\n