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Susquehanna International Group

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Machine Learning Research Internship - PhD: 2027 Susquehanna International Group in United States

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Apr 14, 2027

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Country

United States

University

Susquehanna International Group

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Keywords

Computer Science
Data Science
Signal Processing
Mathematics
Finance
Predictive Modeling
Quantitative Finance
Statistics
Physics
ML

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About this position

Machine Learning Research Internship - PhD: 2027 is a 10-week immersive research opportunity with Susquehanna International Group’s Quantitative Research team in Bala Cynwyd, Pennsylvania.

The internship focuses on machine learning research at the intersection of data, algorithms, and markets. The selected PhD candidate will work on high-impact projects that mirror the workflows of Susquehanna’s full-time research team, applying machine learning and data science to real financial problems in quantitative trading. The role emphasizes building predictive models, extracting signals from noisy and non-stationary datasets, and exploring how advanced ML methods can support strategic execution and model deployment in markets.

The research environment is described as highly collaborative and fast moving, with small teams of researchers, developers, and traders working together on practical problems. Interns will have access to proprietary datasets and substantial computing infrastructure, including a large GPU cluster for computationally intensive training, simulation, and experimentation. The experience is designed to combine hands-on research with mentorship and exposure to Susquehanna’s ML, quant, and trading practices.

The project scope includes model development, experimentation with modern ML frameworks, and the application of rigorous scientific methods to complex financial data. The posting highlights work on alpha generation, signal processing, and risk-aware decision making within a systematic trading environment.

Funding details

Available

What's required

Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field. Applicants should have proven experience applying machine learning techniques in a professional or academic setting, a strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR, and hands-on experience with machine learning frameworks including PyTorch and TensorFlow. Candidates should also show a deep interest in solving complex problems and the ability to innovate in a fast-paced, competitive environment.

How to apply

Apply through the posted MathJobs application link. Submit your application materials via the portal and follow any instructions on the posting.

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