Position available within the research project entitled: “Digital Finance - Reaching New Frontiers (DIGITAL through the Horizon Europe Marie Skłodowska-Curie Actions for Doctoral Networks (MSCA DN). For all instructions and templates to be used during the application phase, it is ESSENTIAL to consult the call for recruitment available at the following link: Call for Recruitment: MSCA Digital Finance Project IRP 9 | www.scienzepolitiche.unina.it.

We are looking for a highly motivated and creative Ph.D. candidate interested in advanced statistical modelling with application in AI-based systems in finance.

From a methodological point of view, the candidate will have to deal with statistical models capable of processing complex data systems. In particular models for categorical longitudinal and multilevel data. From an application perspective, financial decision-makers and AI model builders do not understand the capabilities of XAI or the impact of ESG on society and the economy. This project promotes dialogue and knowledge transfer between these fields. It facilitates innovation and collaboration between AI, sustainable finance and ESG technologies.

During the project, the candidate will closely collaborate with industry and a doctoral training network spread throughout Europe, including extended research stays abroad. 

The successful applicant will join the Dep. of Political Science, University of Naples Federico II.

Background 

This Ph.D. position is the one of the two positions at the University of Naples Federico II and one of 19 in the context of the international Marie Skłodowska-Curie Actions project DIGITAL. For the general description of DIGITAL and the Ph.D. positions, please check https://www.digital-finance-msca.com/.  

DIGITAL's main goal? To significantly advance the methodologies and business models for Digital Finance through the use of five interconnected research objectives https://www.digital-finance-msca.com/: 

1. Ensure sufficient data quality to contribute to the EU's efforts of building 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 state-of-the-art explainable artificial intelligence (XAI) algorithms to financial applications and extend existing frameworks 
4. Design risk management tools concerning the applications of the Blockchain technology in Finance 
5. Simulate financial markets and evaluate products with a sustainability component 

The description here focuses on the specific position " Towards Explainable and Fair AI-Generated Decisions (IRP 9)" (mainly included in objective 1 – WP3 Explainable and fair AI), outlining the project's key take aways and desired skillset of prospective candidates. 

The challenge 

Within this IRP, the candidate will explain the inner workings of algorithms and their interpretation is entirely dependent on the target audience. The existing literature fails to match the growing number of explainable AI (XAI) methods with the varying explainability requirements of stakeholders. To promote the widespread adoption of AI-based systems in finance, additional research is required to map the requirements of explainable systems across the various stakeholders in the finance industry

Among the expected results, we mention the development of advanced statistical models that can solve part of the research questions promoted by public sector  and the private sector (banks and FinTechs companies).

HOW TO APPLY. Applications should be submitted via email to leonese@unina.it, with a cc to ludovicamariafrancesca.danna@unina.it, and the subject line should read "APPLICATION MSCA DIGITAL IRP 9", by the given deadline. In order to be eligible, the online application form must be submitted together with a set of due application documents (CV, COVER LETTER, SELF DECLARATION OF HONOUR), each using the templates provided at the same link of this notice (Call for Recruitment: MSCA Digital Finance Project IRP 9 | www.scienzepolitiche.unina.it).

Furthermore, you must send an academic record with scan of the degree qualifications (Documents proving your educational level and field of study) and a copy of your passport/ID.