PhD Position – Reinforcement Learning: Applications are invited for a PhD position focused on exploring synaptic plasticity rules in the context of few-shot event-based reinforcement learning. This opportunity is part of the Marie Skłodowska-Curie Actions (MSCA) Doctoral Network “ELEVATE” at the Peter Grünberg Institute.
PhD Position – Synaptic Plasticity Rules for Few-Shot Event-based Reinforcement Learning
Designation
PhD Researcher
Research Area
- Neuromorphic Computing
- Reinforcement Learning
- Machine Learning Algorithms
Location
- Peter Grünberg Institute, Forschungszentrum Jülich, Aachen, Germany
Criteria | Details |
---|---|
Position Type | PhD Position |
Duration | 3 years |
Salary | 75% of pay group 13 (TVöD-Bund) + 60% of monthly salary as a special payment (‘Christmas bonus’) |
Annual Leave | 30 days |
Application Deadline | September 19, 2025 |
Eligibility/Qualification
- Master’s degree in Physics, Electrical/Electronic Engineering, Computer Science, Mathematics, or a related field.
- Strong coding skills in neural networks and machine learning frameworks (e.g., PyTorch or Jax).
- Creative and analytical thinking skills.
- Knowledge of integrated circuit design and digital neuromorphic hardware is a plus.
- Proficient in English (spoken and written); German language skills not required.
Description
This research aims to develop an event-driven reinforcement learning algorithm that enhances data efficiency through meta-learning techniques. Candidates will explore digital hardware implementations and participate in internships at TU Delft and Mercedes-Benz. Responsibilities include algorithm development, comparative evaluations of hardware backends, publishing research findings, and supervising student projects.
Key Responsibilities:
- Develop algorithms for event-driven RL with a focus on energy efficiency.
- Collaborate on hardware realizations within spiking neural network designs.
- Publish research articles and present at international conferences.
How to Apply
Interested candidates are encouraged to apply through the designated online application platform (technical applications via email are not accepted). Further details and the application link can be found on the official website.
Last Date for Apply
September 19, 2025
For more information on the application process and FAQs, please visit the official site of the Forschungszentrum Jülich.