Electric Vehicle Fleet Charging Optimization Specialist
5 days ago
Machine Learning and Mathematical Optimization Researcher
Job Description:
We are seeking a highly motivated researcher to join our team in developing machine learning and mathematical optimization solutions for electric vehicle fleet charging optimization under different constraints. The successful candidate will be responsible for formulating and developing machine learning and mathematical optimization solutions for electric vehicle (EV) fleet charging scheduling problems with considerations of various smart power grids, battery degradation, and infrastructure level constraints.
Required Skills and Qualifications:
- Master's degree in Computer Science, Electrical Engineering or related field for Research Associate position
- PhD in smart grids, energy management, or mathematical optimizations for Research Fellow position
- Background in the application of machine learning and mathematical optimization techniques, including reinforcement learning
- Proven publication track record in similar domains for Research Fellow position
Benefits:
This is an excellent opportunity to work on a cutting-edge project that has significant potential for impact. The successful candidate will have the chance to develop their skills and expertise in machine learning and mathematical optimization, and contribute to the development of innovative solutions for electric vehicle fleet charging optimization.
Others:
The role will involve close collaboration with our partner ITB to apply solutions in a local context, using data available with ITB. The successful candidate will also have the opportunity to publish research outcomes in journals of international standing, and attend and present research findings and papers at academic meetings.
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