2 PhD Candidates: Sustainable Energy: The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are seeking 2 PhD Candidates for the Reinforcement Learning Lab for Sustainable Energy, a collaboration between Leiden University and an industrial partner. These positions offer an opportunity to work on cutting-edge research in artificial intelligence and machine learning applied to address challenges in sustainable energy.
2 PhD Candidates, Reinforcement Learning for Sustainable Energy
Summary Table:
- Vacancy Number: 14820
- Job Type: PhD positions
- Hours (in fte): 1.0
- External/Internal: External
- Location: Leiden
- Placed On: 30 April 2024
- Closing Date: 31 May 2024 (30 more days to apply)
Study Area:
Reinforcement Learning for Sustainable Energy
Scholarship Description:
The Reinforcement Learning Lab for Sustainable Energy focuses on developing, implementing, and evaluating new deep reinforcement learning methodology to address challenges in sustainable energy. These positions offer a unique opportunity to work at the forefront of AI research, collaborating with top researchers and industry experts to develop solutions with real-world impact.
Eligibility:
Candidates should hold a master’s degree in Computer Science, Artificial Intelligence, or a related field, with a strong affinity for reinforcement learning and deep learning. Good programming skills and familiarity with sustainable energy transition are desirable. Candidates should also possess excellent research, writing, and teamwork skills.
Required Documents:
- Resume
- Application letter addressing selection criteria and topic preference
- BSc and MSc degree certificates or expected graduation date
- Full grade list for bachelor’s and master’s degrees
- Examples of scientific writing (e.g., thesis, publication, course report)
- Examples of coding skills
- References from university supervisors or scientific collaborators
How to Apply:
To apply, submit your application online via the university website. Ensure that all required documents are attached to your application. Applications must be submitted before May 31, 2024, 23:59 CET to be considered.
Last Date: May 31, 2024
