Principal AI Computational Scientist

Would you like to work at the intersection of AI and healthcare, solving complex computational problems that can transform medicine and deepen our understanding of the biological world?

The newly founded Computational Research and Development group at the Broad Clinical Labs is seeking a Principal AI Research Scientist with expertise in AI and a passion for healthcare. Our mission is to pioneer sustainable, innovative, and impactful approaches to characterize and interpret complex molecular and clinical data in order to advance our understanding of the genome and the mechanisms that drive disease, enabling progress in both biomedical research and clinical applications.

By joining our group, you will work in close collaboration with world-leading molecular and clinical scientists at the Broad Clinical Labs to identify and address the key problems in the field and co-design full-stack molecular and computational solutions. You will also be integrated into the large interdisciplinary community of scientists at the Broad Institute and its numerous affiliated institutions.

About the Role:

As a Principal AI Research Scientist, you will create novel learning-based approaches for the analysis and interpretation of petabyte-scale genomic and clinical datasets. You will design and implement AI solutions for some of the most critical open problems in the field, leveraging data from diverse molecular assays and sequencing platforms.

About You:

You are an innovative and experienced AI researcher with a strong foundation in computer science, driven to make a difference in healthcare. Your expertise includes advanced algorithm design, strong software development skills, extensive experience implementing, training, and benchmarking deep learning models, and substantial experience working with complex large-scale datasets. You are motivated to develop highly robust methods that can be deployed in a real-world clinical setting. You enjoy working closely with scientists from diverse disciplines to design solutions that have a strong mathematical and scientific foundation.

Key Responsibilities:

• Lead the development of novel AI methods to address major challenges in biomedical research and clinical applications.
• Analyze and interpret large-scale multi-modal datasets to unlock new biological insights.
• Design, implement, and optimize deep learning models for diverse data types, including sequence, image, and graph data modalities.
• Develop robust and scalable benchmarks to evaluate model performance.
• Design and compile large-scale training datasets.
• Build, test, release, and maintain high-quality open-source software tools and models.
• Collaborate closely with molecular and clinical scientists.
• Mentor junior researchers and trainees.
• Publish and present your research findings in leading journals and conferences.

Qualifications:

• Ph.D. degree in computer science, mathematics, statistics, computational biology, or a related discipline and 4+ years of experience.
• Extensive hands-on expertise in deep learning.
• Expertise with data modeling, visualization, and debugging at scale.
• Strong software engineering skills.
• A solid track record of research publications.
• Deep interest in healthcare and biological research.