3 дня назад
Machine Learning Internship - PhD: 2027 (Machine Learning)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Internship - PhD: 2027 (Machine Learning): Conducting research and developing machine learning models for noisy, non-stationary financial data with an accent on quantitative trading, predictive modeling, and signal extraction. Focus on designing experiments, applying PyTorch and TensorFlow, and translating ML research into model deployment and risk-aware trading decisions.
Location: Bala Cynwyd (Philadelphia Area), Pennsylvania, United States
Company
is a quantitative trading firm using machine learning, advanced quantitative research, and large datasets to develop systematic trading strategies.
What you will do
- Conduct research and develop machine learning models for noisy, non-stationary data.
- Apply machine learning and data science to financial problems in quantitative trading and finance.
- Collaborate with researchers, developers, and traders to improve existing models and explore algorithmic approaches.
- Design and run experiments using current machine learning tools and frameworks.
- Extract signals from complex datasets and analyze market behavior.
- Explore alpha generation, signal processing, model deployment, and risk-aware decision-making.
Requirements
- Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a related field.
- Professional or academic experience applying machine learning techniques.
- Strong publication record in conferences such as NeurIPS, ICML, or ICLR.
- Hands-on experience with PyTorch and TensorFlow.
- Strong interest in solving complex problems and innovating in a fast-paced environment.
Culture & Benefits
- Ten-week immersive internship starting in June 2027.
- One-on-one mentorship from experienced researchers and technologists.
- Comprehensive education program covering machine learning, quantitative research, and trading.
- Access to financial data and computing resources.
- Collaborative environment with researchers, engineers, and traders.
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