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.

• 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.