Member of Technical Staff, Survival Analysis
Core
Design and implement novel survival analysis methods to predict patient outcomes and treatment response using multi-modal clinical data.
Role type
Research-focused machine learning engineer (survival analysis)
Builds
Clinical AI tools for precision medicine and production-ready code from research papers
Domain
Healthcare / Clinical AI / Survival Analysis
Deliverable
production ML models
Required skills
Survival analysis methods, Python, PyTorch, Deep learning, Statistics, Linear algebra, Probability, Machine learning foundations
Preferred skills
Self-supervised learning, Multi-modal learning, Domain adaptation, Causal inference, Model interpretability, Computational pathology, Publications in A* conferences (ICML, ICLR, NeurIPS, CVPR)
Technologies
Python, PyTorch
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 members of the team
Seniority
Senior, hands-on IC
