Internship in Innovation & Sustainability - For students in the field of Computational Chemistry, Data Science, Computer Science or a related quantitative discipline
Tasks
- Apply uncertainty quantification methods
- Benchmark machine learning models
- Build uncertainty quantification framework
- Collaborate with stakeholders
- Collect data
- Communicate results
- Compare model algorithms
- Develop benchmarking leaderboard
- Evaluate featurization techniques
- Extend models with uncertainty metrics
- Integrate models into MLOps systems
- Prepare data
Perks/Benefits
- N/A
Skills/Tech-stack
Data benchmarking | Deep learning | Featurization | MLOps | Machine Learning | Model Evaluation | PyTorch | Python | Scikit-learn | Software development | Statistical Analysis | System Integration | Uncertainty Quantification
Education
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