PhD position Reinforcement learning for digital finance

The successful applicant will join the Industrial Engineering and Business Information Systems (IEBIS) section of the High-Tech Business & Entrepreneurship Department (HBE) at the Faculty of Behavioural, Management and Social Sciences (BMS).

Background

This Ph.D. position is one four positions at the University of Twente (UT) and one of 19 positions in the context of the international Marie Sk?odowska-Curie Actions project DIGITAL. For the general description of DIGITAL and its Ph.D. positions, please check this page. Information about all other positions is available at EURAXESS, if you would be interested in any of the other positions as well, clearly state that in your cover letter.

DIGITAL' main goal? To significantly advance the methodologies and business models for Digital Finance through the use of five interconnected research objectives:

1. Ensure sufficient data quality to contribute to the EU's efforts to build a single digital market for data;
2. Address deployment issues of complex artificial intelligence models for real-world financial problems;
3.  Validate the utility of pioneering eXplainable Artificial Intelligence (XAI) algorithms to financial applications and extend existing frameworks;
4. Design risk management tools concerning the applications of Blockchain technology in Finance;
5.  Simulate financial markets and evaluate products with a sustainability component.

The challenge

Reinforcement Learning (RL) has become a popular paradigm for automating decision-making under uncertainty in complex environments. Although deep RL has had several breakthroughs in recent years and proven impressive algorithmic performance in closed environments, it has not yet found its way to real-world applications in open environments. In practice, RL algorithms have to work with imperfect data, be integrated into existing ecosystems, and be of use to human decision-makers. Additionally, the financial sector is subject to heavy regulation and high standards concerning risk management, fairness, and explainability. Although successful integration of RL may enhance the quality of decision-making in digital finance, several hurdles need to be overcome. Thus, this Ph.D. project examines how RL can advance digital finance.

You will address several RL implementation issues in digital finance, including both technical challenges and domain-specific ones. Utility-based RL results will improve financial decision-making by developing multi-criteria analysis, extreme scenarios, and risk management methods. RL in decision support will be optimized for explainability, regulatory compliance, model abstractions, and human judgment. We will also examine technological challenges like digital twin environments, machine learning pipelines, and digital finance ecosystem integration.

Are you interested in being part of our team? Please submit your application, and include:

• A cover letter (maximum 2 pages A4), emphasizing your specific interest, qualifications, and motivations to apply for this position;
• A Curriculum Vitae, including a list of all courses attended and grades obtained, and, if applicable, a list of publications and references;
• An IELTS-test, Internet TOEFL test (TOEFL-iBT), or a Cambridge CAE-C (CPE). Applicants with a non-Dutch qualification and who have not had secondary and tertiary education in English can only be admitted with an IELTS-test showing a total band score of at least 6.5, internet. TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE).

The deadline for the application is 30 April 2024.

Additional information can be acquired via email from dr. Wouter van Heeswijk or dr. Joerg R. Osterrieder via email: [email protected].

The HBE cluster is dedicated to encouraging a supportive and inclusive working culture. Our aim is that all job applicants are given equal opportunities. When we select candidates for employment, it will be on the basis of their competence and ability. To support workforce diversity, we are open to offering flexible working conditions on an individual basis to support work-life balance, that may include a contract of employment, working hours and location, or childcare arrangements.

The High Business Entrepreneurship corporate video can be watched via this link .

The Faculty of Behavioral, Management and Social sciences (BMS) aims to play a key role in understanding, jointly developing and evaluating innovations in society. Technological developments are the engine of innovation. As a technical university that puts people first, we tailor them to human needs and behavior and use social engineering to integrate them into society. We also ensure adequate governance at public and private level, and robust, inclusive and fair organizational structures. We do this by developing, sharing and applying high-quality knowledge in Psychology, Business Administration, Public Administration, Communication Sciences, Philosophy, Educational Sciences and Health Sciences. Our research and education in these disciplines revolves around tackling and solving societal challenges. The research programs of BMS are closely linked to the research of the UT institutes Mesa+ Institute for Nanotechnology, TechMed Center and Digital Society Institute.

As an employer, the Faculty of BMS offers work that matters. We equip you to create new possibilities for yourself and for our society. With us, you will become part of a leading technical university with increasing, positive social impact. We offer an open, inclusive and entrepreneurial atmosphere, in which we encourage you to make healthy choices, for example through our flexible, adaptable benefits.