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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

9Open Positions

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Machine Learning Research Internship

G-Research
Found 2 months ago
Location
London, United Kingdom
Duration (Months)
2.5 Months
Time
Full-time
Work Mode
On-site
Salary
Highly competitive compensation plus accommodation
Visa Help
Not disclosed
Last Verified
2 months ago

Education

  • PhD
  • Master

Skills & Qualifications

Technical Skills

  • Machine Learning
  • deep learning
  • reinforcement learning
  • non-convex optimisation
  • Bayesian non-parametrics
  • NLP
  • approximate inference
  • Python
  • scikit-learn
  • SciPy
  • NumPy
  • Pandas
  • Jupyter

Soft Skills

  • Excellent reasoning skills
  • mathematical ability

Job Description

Over the course of 10 weeks, G-Research Summer Research Programme interns gain a unique insight into life as a Machine Learning (ML) practitioner at a leading quantitative finance research firm. Our full-time ML researchers use a wide range of tools and techniques in an applied setting, putting their expertise to use in direct, production-ready applications with immediate results. They have access to vast computing resources and are limited only by their imagination. As an ML intern, you will have the opportunity to experience some of this as part of a 10-week programme working on a meaningful and challenging research project that demands the application of innovative yet pragmatic mathematical and computational analysis. You will be paired with a mentor who will supervise your work and provide ongoing feedback to help you improve and develop, as well as access to senior staff who are leaders in their fields. Your internship will culminate in a final presentation of your research ideas to senior management. Taking part in G-Research's Summer Internship Programme will give you an in-depth insight into our academic approach to the world of quantitative finance and allow you to explore the thriving city of London, while you get to know your fellow interns and colleagues through a full itinerary of fun social events. Top performers on the programme will be considered for full-time opportunities on completion of their studies.

Requirements

  • A post-graduate degree in Machine Learning or a related discipline, or commercial experience developing novel machine learning algorithms
  • exceptional candidates with a proven record of success in online data science competitions, such as Kaggle
  • PhD level study is preferred
  • Experience in one or more of deep learning, reinforcement learning, non-convex optimisation, Bayesian non-parametrics, NLP or approximate inference
  • Excellent reasoning skills and mathematical ability are crucial
  • Strong programming skills and experience working with Python, scikit-learn, SciPy, NumPy, Pandas and Jupyter
  • an interest in finance and the motivation to rapidly learn more is a prerequisite for working here

Related Field

  • Quantitative Finance

Related Subfield

  • Quantitative Research

Languages

  • English

Nice to Haves

  • interest in finance
  • motivation to rapidly learn more
▶Apply Now

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