kadence · 9 hours ago
Artificial Intelligence Researcher (Clinical Multimodal & Longitudinal EHR)
United States
Full-time
Remote
Senior LevelKadence is partnered with an AI x Bio company hiring an AI Researcher to develop and evaluate machine learning models using longitudinal EHR and multimodal clinical data. The role involves building models that learn patient representations over time and integrating structured & unstructured clinical signals to support prediction, phenotyping, and real-world clinical applications.
Hiring Manager
Ryan Burton
Responsibilities
Design and train models on longitudinal EHR (irregular time series, missingness, temporal validation)
Develop multimodal clinical ML combining structured EHR & clinical notes, and ideally imaging, waveforms, omics, claims, or wearables
Build representation learning approaches (e.g., transformers, self-supervised/contrastive learning, multimodal fusion, LLM-based systems)
Run rigorous experiments, benchmarking, and ablation studies; document results clearly
Partner with clinical/data stakeholders to define cohorts, outcomes, and evaluation protocols
Qualification
Required
PhD in ML/CS/Stats/Biomed Informatics/Computational Biology (or equivalent research background)
Industry experience applying ML to real-world datasets and products
Proven experience with EHR/clinical data and longitudinal modeling
Experience building multimodal models across multiple clinical modalities
Strong Python + deep learning framework skills (PyTorch preferred)
Strong research rigor and ability to communicate findings clearly
Preferred
Publications in top ML/health venues
Familiarity with healthcare data standards: ICD, CPT, LOINC, RxNorm, SNOMED, OMOP, FHIR
Experience with model calibration, generalization, fairness, interpretability, or privacy-preserving ML
Company
kadence
Kadence - We place elite AI talent at the intersection of science & engineering, from PHD to Executive.
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase