22 часа назад
Machine Learning Internship - PhD: 2027
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Internship - PhD: 2027 (Machine Learning/Quantitative Finance): Conducting research and developing ML models for noisy, non-stationary financial data with an accent on predictive modeling, signal extraction, and algorithmic trading. Focus on designing experiments, developing research-driven models, and deploying risk-aware machine learning approaches for quantitative finance.
Location: U.S.-based 10-week internship with full-time placement in the Hong Kong office upon graduation
Company
is a global quantitative trading firm using machine learning, advanced quantitative research, and large-scale 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 quantitative trading and financial problems.
- Collaborate with researchers, developers, and traders to improve models and explore algorithmic approaches.
- Design and run experiments using modern machine learning tools and frameworks.
- Extract signals from complex datasets and analyze market behavior using rigorous scientific methods.
- Explore applications including 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 closely related field.
- Professional or academic experience applying machine learning techniques.
- Strong publication record in top-tier 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
- One-on-one mentorship from experienced researchers and technologists.
- Comprehensive education program covering machine learning, quantitative research, and trading.
- Access to extensive financial data and computing resources.
- Opportunity to contribute directly to trading performance.
- Collaborative environment with researchers, engineers, and traders.
- Visa sponsorship is available.
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