AI Scientist - BioMedical AI

Key ResponsibilitiesDesign, train, and refine foundational models specifically tailored to perturb-seq and other single-cell datasets. Build pipelines for preprocessing, normalization, and integration of extensive single-cell and perturbation data. Utilize machine learning and AI methodologies to model cellular responses to perturbations, identifying causal biological insights. Work in collaboration with experimental biologists to ensure alignment between computational methods and experimental design, as well as discovery objectives. Develop multimodal integration techniques across transcriptomic, epigenomic, and proteomic single-cell readouts. Publish methodologies and findings in prestigious scientific journals and represent the company at conferences. QualificationsPhD or equivalent in Computational Biology, Computer Science, Bioinformatics, or a related field. Extensive expertise in single-cell data analysis, particularly with perturb-seq. Hands-on experience with foundational models or large-scale self-supervised learning techniques (e.g., transformers, variational autoencoders). Proficient coding skills in Python, familiar with ML frameworks (PyTorch/TensorFlow), and single-cell analysis tools (Scanpy, Seurat). Experience in developing scalable machine learning methods for large biological datasets. Preferred QualificationsBackground in working with clinical data or translational research. Strong communication skills and ability to work collaboratively in a team-oriented environment.