Founding Scientist — Generative & Causal ML for Healthcare
Core
Design and build generative and causal ML models to create realistic, high-fidelity scenarios for complex real-world healthcare environments.
Role type
Founding Scientist (Generative & Causal ML)
Builds
Synthetic intelligence capabilities and production-ready ML features for healthcare AI
Domain
Healthcare AI, Generative Modeling, Causal Inference
Deliverable
production ML models
Required skills
Generative modeling, Data fusion, Multimodal models, Federated learning, Privacy-preserving training, Medical ontologies (SNOMED, LOINC, RxNorm), Knowledge graphs, Production-grade code development
Preferred skills
Hybrid classical-quantum methods (Qiskit, PennyLane), OMOP/FHIR standards, Real-world irregular time series
Technologies
Qiskit, PennyLane
Responsibilities
Design models for structured, temporal, multimodal, and causal data; Build, train, and evaluate ML architectures; Support distributed or federated learning; Develop privacy-preserving training and evaluation methods; Establish reproducibility, versioning, and testing standards; Optimize models for constrained environments
