AI Research Scientist

Responsibilities Develop, train, and evaluate large-scale AI/ML models across diverse biological data types. Investigate new modeling paradigms to address open biological research questions. Translate complex scientific questions into computational frameworks, experiments, and benchmarks. Assess model behavior and interpretability in scientific contexts. Design and run experiments at scale with benchmarking and model analysis. Build reusable modeling frameworks and document methods for reproducibility. Qualifications PhD in Computer Science, Applied Mathematics, Statistics, Computational Biology, or a related field; or equivalent combination of degree and experience. Demonstrated experience developing and evaluating novel AI/ML approaches for complex, large-scale datasets. Proficiency in Python and modern deep learning frameworks (e.g., PyTorch, JAX). Strong foundation in machine learning, deep learning, and scientific computing, including experimentation, benchmarking, and model analysis. Research experience applying machine learning to biological, genomic, or other life‑science data is preferred. Familiarity with large‑scale training and evaluation environments and scientific computing libraries. #J-18808-Ljbffr