We are a research training group driven by the opportunities of the data age. As an interdisciplinary team, we embrace the complexity of real-world problems—messy, incomplete, and often ill-defined—and train our Ph.D. researchers to do the same. Our program equips high-potential candidates with the skills to address challenges at the intersection of Artificial Intelligence, Data Science, and Business. Through specialized coursework, close mentorship, and access to unique high-frequency datasets, we prepare the next generation of scholars to turn data into insight—and insight into impact.

Our approach is grounded in data-driven decision-making. We combine machine learning, modern econometrics, and economic thinking to reduce uncertainty and support better decisions in complex systems. While our methods are applicable across a wide range of industries, our research is particularly rooted in financial and option markets—where data volume, modeling depth, and business relevance converge. Ph.D. candidates gain hands-on research experience, engage in publication-focused projects, and develop the technical and analytical skillset to thrive in both academia and industry.

The KABFI Ph.D. community is proudly international, with researchers from Vietnam, Iran, China, the USA, Germany, and more. Many of our Ph.D. students combine their research with part-time roles at KIT, international institutions, or within industry. Their diverse academic backgrounds—from finance and economics to computer science and engineering—reflect the interdisciplinary and applied nature of the program, and their career paths reflect its practical relevance and global outlook.

Advance Your Ph.D. in AI, Business & Finance with KABFI:

Join a community of bright and driven PhD researchers at KABFI (pronounced “cab-fee”)—KIT’s AI, Business, and Financial Markets Insights PhD Research Training Group—dedicated to pioneering the synergy of artificial intelligence, financial markets, and cutting-edge business applications. KABFI welcomes a select group of individuals with a passion for rigorous research, a strong foundation in data and markets, and a vision to shape the future of AI-enhanced decision-making in business and finance. For those interested in deepening their mathematical and computational focus, collaboration with other KIT programs—such as the Graduate School Computational and Data Science (KCDS)—offers additional opportunities for interdisciplinary PhD research. 

Program Overview:

• Academic Aim: At KABFI, we foster a collaborative research culture where incoming Ph.D. students are mentored by a professor and more senior PhD students. Our goal is to support joint, high-impact publications in leading international journals across financial economics, machine learning, artificial intelligence, and statistical modeling. Previous KABFI research has appeared in prestigious journals such as The Review of Financial Studies and The Review of Derivatives Research.

• Financials:  KABFI offers a tuition-free Ph.D. education. Ph.D. researchers are responsible for their own living expenses. To support this, we assist in securing scholarships and part-time positions both within KIT and through industry partners. In recent years, KABFI doctoral students have successfully obtained competitive scholarships, programming positions, and research assistantships.

• Admission:  We welcome applications from motivated and talented candidates year-round. Applicants with a Master’s degree in a relevant discipline and strong academic performance (typically ranging from 'good' (B) to 'very good' (A)) are encouraged to apply. Exceptional Bachelor’s degree holders—particularly those ranked among the top 5% of their cohort—are also invited to apply. Please submit your CV, a motivation letter, and academic transcripts to: kabfi ∂does-not-exist.fbv kit edu

• Coursework: KABFI students complete core training modules and actively engage in weekly research discussions:

• Financial Data Science (9 ECTS): An advanced Bachelor-level exploration into the art and science of working with financial data. https://risk.fbv.kit.edu/c-ram/2297.php
• Advanced Machine Learning and Data Science (9 ECTS): A hands-on, coding-oriented research project bridging AI and finance. https://risk.fbv.kit.edu/c-ram/2307.php
• Deep Financial Economics: A weekly seminar series where students critically assess the impact and quality of recent publications in AI, financial economics, and data science. https://risk.fbv.kit.edu/c-ram/2307.php

            Students without prior academic training in finance may attend selected MBA-level focus weeks. These modules cover essential foundations in:

• Global Financial Markets
• Financial Economics for Data Scientists
• Machine Learning for Data-Driven Decision Making
• Engineering Aspects of Financial Markets
• Alternative Data and Machine Learning for Business Applications

• Relocation & Flexibility: While we strongly encourage Ph.D. researchers to join us on campus in Karlsruhe to benefit fully from the academic environment, select hybrid arrangements have proven successful in the past. We remain open to flexible models for outstanding candidates, especially where professional or personal circumstances require it.

Fast Track Options at KABFI:

The KABFI Ph.D. program offers two Fast Track pathways for exceptional students who wish to accelerate their academic journey and research career.

1. Direct Entry from Bachelor’s Degree

Outstanding Bachelor students—those who can demonstrate they are in the top 5% (95th percentile) of their cohort—have the opportunity to enter the KABFI Ph.D. program directly, without completing a Master’s degree. This route is designed for highly motivated candidates with strong quantitative skills and academic maturity. In such cases, we anticipate that the Ph.D. thesis can be submitted shortly after their peers complete their Master’s studies. All formal requirements of the applicable Promotionsordnung (https://www.sle.kit.edu/downloads/AmtlicheBekanntmachungen/2018_AB_002.pdf) apply.

2. Integrated Fast Track for KIT Students

KIT Bachelor and Master students who aim for an early start in research can follow an integrated Fast Track. These students complete the KABFI core Ph.D. coursework (see “Coursework” section) during their MSc studies at KIT. Additionally, if both the BSc and MSc thesis are written in collaboration with KABFI researchers (implying serious KABFI research efforts during their BSc and MSc studies), it is typically possible to submit the Ph.D. thesis within 18 months of MSc graduation.

Research and Facilities:

• Research Support: At KABFI, Ph.D. researchers benefit from access to state-of-the-art high-performance computing clusters and a broad range of financial databases covering both U.S. and European markets. A particular strength of our infrastructure is our proprietary tick-by-tick option analytics database and complete order book data for all assets traded on Europe’s largest exchange. To ensure a smooth start, more senior Ph.D. students offer hands-on guidance and coaching—an integral part of our mentoring culture designed to help you unlock your full research potential.

• Research Topics: Our research spans a wide range of interdisciplinary fields, with applications in financial economics and engineering, computational risk and asset management, and machine learning for capital market analytics. Topics include the development of supervised learning techniques to address complex business challenges, as well as the design of autonomous systems using financial reinforcement learning. Ph.D. candidates are supported by experienced researchers who meet them at their current level and help them grow into independent scholars equipped to make meaningful contributions in both academia and industry. 

Life After KABFI:

KABFI alumni have received multiple job offers even before completing their dissertations—often choosing between roles in international financial hubs and high-impact positions closer to home. Our graduates have gone on to pursue careers in quantitative finance, asset and risk management, consulting, and AI-driven entrepreneurship.

For Our Corporate Partners: Fostering Research Excellence and Developing Future Talent Together

We gratefully acknowledge the generous support of our corporate partners, whose contributions—often made via the Forschungsgesellschaft Geld-Banken-Bausparkassen-Versicherungen am KIT e.V. (www.fog-am-kit.de)—help make doctoral research scholarships at KABFI possible. These funds enable us to support outstanding Ph.D. candidates from around the world. Among the scholarship recipients to date are three international researchers from Vietnam, Iran, and China, all of whom are women—an encouraging example of the diverse talent that thrives within the KABFI program.

We extend our sincere thanks to Landesbank Baden-Württemberg (LBBW) for its generous financial support of doctoral scholarships, and to Deutsche Börse Group for its invaluable contribution of historical and real-time order-book data covering all assets traded on Xetra, Eurex, and EEX—critical infrastructure for advanced research in capital markets.

KABFI offers companies a unique opportunity to engage with a high-potential research environment focused on data-intensive business challenges through applied, interdisciplinary research.

We invite you to consider the following forms of collaboration:

• Sponsoring Scholarships
  Help foster the next generation of researchers in AI and data-driven business applications. Corporate sponsorships enable outstanding candidates to pursue their Ph.D. at KIT. Regular updates and mutual exchange ensure that research insights remain connected to real-world business challenges and innovation goals.
• Developing In-House Talent
  Selected corporate partners have chosen to support their own employees in pursuing a Ph.D. within the KABFI framework—typically through a 50% employment model. This format allows participants to remain professionally engaged while contributing to academically rigorous and industry-relevant research.
• Offering Part-Time Opportunities to KABFI Scholars
  We welcome collaboration with companies interested in offering research-oriented part-time employment to KABFI doctoral candidates. These partnerships provide valuable practical experience for the students and bring fresh, data-driven perspectives into your organization.

If your organization is interested in exploring a partnership with KABFI, we would be pleased to speak with you.

 Contact: kabfi ∂does-not-exist.fbv kit edu