PHD Graduate Student

PhD position available in Applied Machine Learning, Reinforcement Learning, Optimization, and Control applied to energy arbitrage, sustainable energy systems, and managing renewable uncertainties via battery storage.

Faculty:

Research area(s):

Project overview:

The work involves addressing challenges such as mitigating uncertainties in renewable generation with battery storage systems, achieving energy-efficient and carbon-efficient operation of HVAC and other electrical appliances to reduce peak energy loads and carbon footprint (thus obtaining sustainable and decarbonized energy consumption), and the use of battery storage systems for energy arbitrage.

The selected candidate will have the flexibility to focus on one or more of these challenges, depending on interest and expertise. The work will involve tools and techniques from machine learning, reinforcement learning, stochastic modeling (including applied probability and Markov chains), optimization, and control theory.

Desired candidate profile:

We are looking for a motivated candidate who possesses:

• A strong foundation in mathematics
• A willingness to learn and apply methods from reinforcement learning, machine learning, probability, and sequential decision-making
• An interest in solving real-world energy problems through advanced computational and analytical methods

Required qualifications and skills:

1. A Master’s degree or a four-year Bachelor’s degree in Mathematics, Electrical Engineering, Electronics, Communication, Computer Science, or a related discipline.
2. A strong background in mathematics. Candidates with prior exposure to reinforcement learning, machine learning, and applied probability are strongly encouraged to apply.
3. Proficiency in programming in Python or MATLAB.

More details about the eligibility criteria can be found here: https://plaksha.edu.in/phd

How to apply: