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 Postdoctoral Associate 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 Postdoctoral Associate you will develop novel algorithms and 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 AI researcher with a strong foundation in computer science driven to make a difference in healthcare. Your expertise includes algorithm design software development implementation training and benchmarking of deep learning models and 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:
Develop 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
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
Hands-on expertise in deep learning
Proficiency in 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
Kindly Include a cover letter along with your resume.
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