The AI/ML Sequence Learning Team applies machine learning and AI methods to biological sequence (DNA, RNA, protein) data from large-scale human genetic, functional genomic and single-cell experiments.
Models operating directly on sequence data that can infer how variants alter protein/RNA abundance, structure, and function have the potential to be transformative in drug discovery, empowering us to find new life-saving medicines.
Requirements & Skills:
Graduate studies in Computer Science or Applied Math, undergraduate studies in Computer Science and relevant graduate studies in the life sciences with a focus on AI/ML techniques, or undergraduate studies in Computer Science and equivalent work history.
Experience in software engineer with Python.
Experience with PyTorch, Tensorflow, or other deep learning frameworks.
Experience in ML stack.
PhD in computer science.
Knowledge in disease biology, molecular biology, and biochemistry
Experience with biological data (e.g., genomics, transcriptomics, epigenomics, proteomics)
Understanding and application of best practices in Machine Learning
Track record of contributing to open-source projects
