Explore physics-inspired neural network compression as a Research Associate with Amii, using Python and PyTorch for rigorous computational experiments.

Amii seeks a Research Associate for SPAARC, a collaboration with the European Space Agency. You will investigate statistical physics and renormalization-group ideas alongside machine learning, knowledge distillation, and architectural optimization. The work examines how neural network architectures and performance evolve under constrained computational resources.

Key Responsibilities:

- Develop theoretical foundations for renormalization-group approaches to compression
- Evaluate models and algorithms for compression and knowledge distillation
- Design numerical experiments on scaling and compression limits




- Build research software and machine learning pipelines
- Analyze uncertainty, robustness, and architectural sensitivity

Requirements:

- PhD in Physics or Mathematics, or exceptional equivalent expertise
- Extensive experience designing, training, and evaluating neural networks
- Strong Python and up-to-date framework skills, particularly PyTorch
- Experience with statistical analysis and reproducible computational experiments
- Legal eligibility to work in Canada

Apply physics, Python, PyTorch, and quantitative research to neural network compression with Amii and ESA.

📌 Physics-Inspired Machine Learning Research Associate (Edmonton)
🏢 Alberta-Machine-Intelligence-Institute-1
📍 Edmonton