Data Science Intern

Lightsource bp

London, United Kingdom
Competitive salary; annual bonus; retention bank, ...
On-site
Reinforcement learning experience
Constrained optimization modeling
Python scientific computing toolkit
This internship is designed for a PhD-level researcher to apply cutting-edge methods to real-world energy systems within a global renewable energy organization

Job Summary

  • This internship is designed for a PhD-level researcher to apply cutting-edge methods to real-world energy systems within a global renewable energy organization.
  • You will contribute to research, design, experiment, implement, and test approaches including modeling, simulation, reinforcement learning, and optimization to support improved operational decision-making for battery energy storage systems.
  • The role offers exposure to high-impact projects, collaboration with experienced AI practitioners, and opportunities to publish, innovate, and drive the company's AI roadmap forward.

Matching Summary

This internship is designed for a PhD-level researcher to apply cutting-edge methods to real-world energy systems within a global renewable energy organization.

Salary

Competitive salary; Annual bonus; Retention bank, health insurance, pension

Skills & Requirements

Must-have

  • Reinforcement learning experience
  • Constrained optimization modeling
  • Python scientific computing toolkit
  • PyTorch and RL frameworks
  • Sequential decision-making frameworks

Nice-to-have

  • Energy systems domain knowledge
  • Grid flexibility markets understanding
  • Strong communication skills
  • Agile working environment experience
  • Curiosity and autonomy

Key Requirements

  • Currently pursuing PhD in quantitative field
  • Master's degree required as minimum
  • Equivalent experience in RL or optimization

Work Rights

Not specified

Tailored Resume

Cover Letter