Member of Technical Staff, Survival Analysis
Conducts research and develops production-ready survival analysis and machine learning methods for clinical AI, including evaluation frameworks and research publications. Requires a PhD in machine learning or statistics, strong statistical foundations, and expertise in Python and PyTorch.
About the job
Responsibilities
- Design and implement novel survival analysis methods.
- Translate machine learning papers into production-ready code.
- Build robust model evaluation frameworks.
- Disseminate results by co-authoring research papers and abstracts.
- Collaborate with a multidisciplinary team of engineers and scientists.
- Co-mentor junior team members.
Requirements
- PhD in machine learning or statistics.
- Excellent knowledge of survival analysis methods.
- Passion for research, attention to detail, and ability to drive tasks to completion.
- Strong preference for papers in A* conferences such as ICML, ICLR, NeurIPS, or CVPR, or in top-tier statistics journals.
- Excellent understanding of core machine learning concepts.
- Excellent knowledge of statistics, linear algebra, probability, and machine learning foundations.
- Excellent Python and PyTorch skills.
- Experience in deep learning.
Nice-to-Haves
- Self-supervised learning.
- Multimodal learning.
- Domain adaptation.
- Causal inference.
- Model interpretability.
- Computational pathology.
Skills
Survival Analysis, Machine Learning, Statistics, Python, PyTorch, Deep Learning, Linear Algebra, Probability, Self-Supervised Learning, Multimodal Learning, Domain Adaptation, Causal Inference, Model Interpretability, Computational Pathology
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