Graduate Research Assistant, Quantitative and Systems Health Services
UT MAIN CAMPUS, United States
USD 43K-44K (estimate) Entry-level Part Time
Tasks
- Benchmark baseline machine learning models
- Build common data elements
- Build machine learning pipelines for clinical prediction
- Construct knowledge graphs for disease areas
- Develop data preprocessing pipelines
- Fine-tune large language models
- Implement feature engineering pipelines
- Maintain open-source code repositories
- Map observational healthcare data to data standards
- Perform missing data imputation
- Prepare manuscripts for conference submission
- Prompt engineer and evaluate large language models
- Write technical documentation
Perks/Benefits
- N/A
Skills/Tech-stack
Deep learning | Graphical Models | Language Processing | Linear Algebra | Machine Learning | Multivariable Calculus | Natural Language | Natural Language Processing | NumPy | Pandas | Probabilistic Graphical Models | Probability theory | PyTorch | Python | Scikit-learn | Statistical inference | TensorFlow | Transformer Models
Education
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