Susquehanna International Group
Just Landed
New Today
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
Country
United States
University
Susquehanna International Group
Apply for this position
Keywords
Suggested positions
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.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.