Rethinking risk management: Shape the future of the financial world as a master's student

Stellenbeschreibung:

Rethinking risk management: Shape the future of the financial world as a master's student

The Fraunhofer Institute for Industrial Engineering IAO invites you to immerse yourself in the exciting world of quantitative risk management. Our "Quantum Computing" team is investigating how companies can make effective use of quantum computers in the future and is developing suitable software solutions, algorithms, and tools for these applications. Utilize state‑of‑the‑art ML architectures such as transformers and reinforcement learning to play a key role in optimizing risk management strategies.

What You Will Do

Implementation of ML models for optimizing hedging strategies in Python
Evaluation and comparison of different models (benchmarking)
Supporting data preparation and analysis for ML models
Assisting with the documentation and presentation of project results
Researching current trends and technologies in the field of ML and finance

What You Bring To The Table

You are a registered student in the field of computer science, quantitative finance, (quantum) physics, mathematics, or similar areas and are looking for a topic for your master’s thesis
In‑depth knowledge of ML (e.g., RNNs, LSTMs, transformers, RL)
Initial experience with relevant Python libraries (e.g., TensorFlow, PyTorch, RLlib)
Basic understanding of finance topics, especially derivative pricing, is an advantage but not required
Interest in new research topics in ML and finance
Creative, independent way of working
Ideally, you are willing to be present at the office in Stuttgart on a regular basis

What You Can Expect

Exciting and innovative projects with insights into quant finance, ML, and quantum computing
Access to the latest development technologies
Interesting, practical tasks that will help you expand your skills
A pleasant working atmosphere in a motivated team
Equal opportunities, accessibility, and diversity
State‑of‑the‑art technology and working environment
Mobile working and flexible working time models, and only 10 minutes away from the university
Transparent and fair remuneration
Connection to our student network
Sports facilities at the University of Stuttgart

Equal Opportunity

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.