PhD Researcher in Machine Learning for Power Electronics (Remote)

Job summary

This position offers a fully funded 3-year PhD opportunity focused on developing machine learning methods for enhancing power electronic converters and motor drives. The role is part of a European Research Council project aimed at embedding intelligence in grid-connected systems to support the green energy transition.

Qualifications

• A two-year master's degree (120 ECTS points) or equivalent academic level.
• Knowledge in computer science and machine learning.
• Familiarity with electrical and electronic engineering principles.
• Proficiency in programming languages such as Python, C++, or MATLAB.
• Strong problem-solving abilities and experience working in interdisciplinary teams.
• Excellent English communication skills, capable of presenting research findings in scientific papers.

Responsibilities

• Develop machine learning methods for reliable training on streaming data.
• Work on physics-informed models, Bayesian modeling, and stochastic optimization.
• Collaborate with stakeholders to address complex challenges in power electronics.

Skills

• Strong analytical and computational skills.
• Ability to work collaboratively in a diverse team environment.
• Effective communication and presentation skills.

Education

• A master's degree in a relevant field is required.

Tools

• Programming languages: Python, C++, MATLAB.
• Machine learning frameworks and tools relevant to power electronics.