Postdoctoral Research Associate in Reliable Neuromorphic, Classical, and Quantum AI
Tasks
- Apply conformal prediction for reliable inference
- Conduct reliable AI research
- Conduct theoretical analysis using statistical learning theory
- Design quantum machine learning reliability frameworks
- Develop calibration and reliability monitoring algorithms
- Develop neuromorphic spiking neural models
- Implement uncertainty quantification
- Mentor PhD students and research assistants
- Perform offline and online model calibration
- Prepare project deliverables and funding proposals
- Present findings at workshops and symposia
- Publish research results in leading journals and conferences
- Use online convex optimization for adaptive decision making
Perks/Benefits
- Access to continuous professional development
- Annual leave
- Cycle scheme
- Employee assistance programme
- Eye test reimbursement
- Private medical insurance
Skills/Tech-stack
Conformal Prediction | Convex Optimization | Hyperparameter Optimization | Hypothesis Testing | Learning Theory | Machine Learning | Model calibration | Multiple Hypothesis Testing | Neural Networks | Neuromorphic Computing | Online convex optimization | Python | Quantum Machine Learning | Spiking Neural Networks | Statistical Learning | Statistical Learning Theory | Statistical modeling | Uncertainty Quantification
Education
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