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We are looking for a highly motivated and creative Ph.D. candidate interested in topics at the intersection of machine learning for macroeconomic forecasting and causal inference. This Ph.D. project aims to benchmark various forecasting methods and then implement a robust tool for causal modeling drawing from recent advances in both fields. During the project, you will closely collaborate with industry and a doctoral training network spread throughout Europe, including extended research stays abroad. 

The successful applicant will join the Data Science Team within Cardo AI, with the degree conferred in collaboration with the WU Vienna University of Economics and Business.


This Ph.D. position is one of 2 positions at Cardo AI 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 the official project webpage.  

DIGITAL’s 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 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 outcomes from this individual research project will contribute to the expanding body of knowledge concerning the applications of cutting-edge machine learning and artificial intelligence techniques to traditional financial problems. Recent findings from the ML literature on time series forecasting will be applied in the first phase of the project. In the second phase of the project, the successful candidate will be able to conduct research in the field of causal inference in finance, which also is a very promising field of research.

The challenge

Macroeconomic factors such as central bank interest rates, inflation, unemployment rates, and house price indices play a crucial role in financial markets, presenting both challenges and opportunities for forecasting. This project is designed to tackle the complexity of predicting these macroeconomic indicators’ future values by benchmarking a variety of methodologies spanning from classical statistical learning to modern machine learning techniques. The initial phase of the project will focus on leveraging recent advancements in machine learning literature to accurately predict these indicators, setting the stage for more informed financial analysis and decision-making.

The longer term objectives of this project extend beyond mere prediction, exploring future market scenarios in a counterfactual fashion and, more generally, delving into causal inference in  econometrics.

Your profile

We look for a highly motivated, enthusiastic researcher who is driven by curiosity and has/is: 

General skills: 

Project-specific skills:

Interested and motivated candidates are encouraged to apply, even when not yet possessing all desired skills. Through self-driven learning and doctoral training, you will be able to develop relevant skills on the job.  

Our offer

Benefits offered as part of this position include: 

  1. Living allowance of EUR 2171/person month (net), Mobility allowance of EUR 600/person month, Family allowance of EUR 660/person month. More details on the allowances can be found here.
  2. Company-provided laptop, monitor, keyboard and mouse, flexible working time, work from home or office, internal and external education as per the set OKR/KPIs guided by mentors, meal vouchers of EUR 5 for each working day.
  3. This PhD position includes two research stays at industrial partners. The first stay will be at the Fraunhofer Institute for Industrial Mathematics in Kaiserslautern (Germany), under the supervision of Prof. Dr. Ralf Korn. It is scheduled to start on Month 18 and last for 4 months, during which exposure to a world-leading research centre, infrastructure and applied industry-research will be provided.  The second stay will be carried out at WU Vienna University of Economics and Business in Vienna (Austria), under the supervision of Prof. Dr. Kurt Hornik and Dr. Ronald Hochreiter. It is scheduled to start on Month 24 and last for 18 months, covering theoretical modeling and mathematics for deep learning.
    1. Any potential change from the initial plan regarding research stays will be dully notified to candidates and reflected in the job advert description.

How to apply

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

Please ensure that your application is submitted by the deadline and note that we will start conducting interviews with short-listed candidates starting from April 2024; however, the application deadline is the 5th of July 2024. Do not make submissions via email as they will not be considered.  

Additional information can be acquired via email from Dr. Gennaro Di Brino (gennaro.dibrino@cardoai.com) with a cc to Dr. Jorg R. Osterrieder (jorg.osterrieder@utwente.nl). 

Diversity and Inclusion

We encourage applications from minorities and underrepresented groups to enrich our diverse academic community. Candidates will be selected on the basis of their competence and ability, and all applicants will be given equal opportunities. We acknowledge the importance of diversity and inclusion for innovation and excellence in digital finance research.

About the department

The Cardo AI Data Science Team includes people with world-class backgrounds in hard science and engineering. The team is structured around our main areas of activity, and it consists of three units: Pricing and Optimization, Tabular Data Modeling, and Unstructured Data Modeling. We work on a diverse range of problems, from Portfolio Optimization (loans, notes, etc.) to Probabilistic Classification (e.g., probability of default), from Time Series Forecasting to Language Modelling. Our mission is to assist decision makers in structured finance markets with the latest, most reliable modeling techniques available in machine learning and quantitative finance research.

About the organization

Cardo AI is a Milan-based software, data, and intelligence company innovating the asset based finance and private credit market. Founded in 2018, our solutions have been designed to help investors, issuers, servicers and lenders unlock opportunity from complexity and transact faster, better, and with lower costs. As of January 2024, our platform manages over $24bn in complex credit assets, standardizing over +35bn data points coming from 130+ systems all over the world.

Ready to Redefine Work? Join Cardo AI and let boldness and creativity reign. Together, we’ll shape the future of fintech! Apply now.