-
outstanding candidates from other fields with rigorous training in mathematics and physics if they are strongly motivated to study the atmosphere and climate. Demonstrated ability to address significant
-
on physiologic waveform analysis, biomedical signal processing, and computational modeling of continuous clinical monitoring data. The successful candidate will work on projects involving the analysis
-
and AI-based approaches, including predictive modeling, stratification, explainable AI, and integrative multimodal analysis. The scholar will have opportunities to lead first-author publications
-
(1-2) Applicants with expertise in one or more of the following areas are encouraged to apply: * Foundation Models * Agentic AI * Reinforcement Learning * Medical Image Analysis Position 2: Intelligent
-
, electrical engineering, cognitive science, applied mathematics, physics, or a related field. Strong computational background and hands-on experience building AI/ML models. Expertise in modern architectures
-
global collaborators, with deployment opportunities ranging from agricultural landscapes in California to tropical wetland ecosystems in Brazil and Indonesia. The ideal candidate has strong data analysis
-
care for patients requiring urgent or emergent intervention. The fellowship provides comprehensive training in data engineering, exploratory analysis, statistical modeling, machine learning, and artificial
-
experimental platform for spatial multi-omic analysis of biological tissues. Our lab builds biological measurement infrastructure—engineering systems that standardize how information is extracted from complex
-
(GitHub) and AI coding assistants (e.g., Claude Code) Strong mathematical foundation relevant to quantitative image analysis (optimization, regression, statistics, signal processing, cluster analysis