Internal Research Fellow (PostDoc) in Theory of Deep Learning
Tasks
- Analyze expressivity optimization generalisation and robustness
- Collaborate on interdisciplinary space related research
- Develop theoretical frameworks models and analytical tools
- Propose original deep learning theory research
- Publish in peer-reviewed journals and conferences
- Quantify uncertainty interpretability and reliability
- Share tools software and methodological developments via open source
- Study representation learning continuous time neural architectures
- Translate theoretical advances into algorithms and prototype tools
Perks/Benefits
Skills/Tech-stack
Bayesian deep learning | Continuous Normalizing Flows | Control Theory | Deep learning | Flow matching | Generalization | Graph Neural Networks | Information theory | Machine Learning | Mathematical Modeling | Neural Networks | Neural ODEs | Normalizing flows | Numerical Methods | Optimal transport | Optimization | Probabilistic Numerics | Representation Learning | Scientific machine learning | Simulation | Statistical Mechanics | Thermodynamics of Learning | Uncertainty Quantification
Education
Roles
Fellow | Postdoctoral Researcher | Research Fellow | Researcher
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