This Research Fellow role focuses on advancing digital pathology through artificial intelligence and machine learning. The position involves working with large-scale digital pathology data and multimodal clinical datasets to develop innovative diagnostic and predictive tools. The fellow collaborates with a multidisciplinary team of AI scientists, engineers, and pathologists to design and implement cutting-edge models and translate research into clinical applications. This role emphasizes both technical development and research leadership, contributing to the future of pathology and healthcare innovation.

Responsibilities:

• Develop, implement, and evaluate AI and machine learning models for digital pathology
• Design and lead research projects in collaboration with cross-functional teams
• Work with large-scale imaging and multimodal clinical datasets
• Develop software tools and algorithms to support clinical insights
• Translate research findings into real-world healthcare applications
• Contribute to publications, presentations, and scientific communication
• Support growth and innovation within the digital pathology research team

Qualifications:

• PhD in Computer Science, Machine Learning, Engineering, Physics, Applied Mathematics, or related field
• Strong background in deep learning methods such as CNNs and transformers
• Proficiency in Python and machine learning frameworks such as PyTorch or scikit-learn
• Experience with systems-level programming languages such as C, C++, or Rust
• Strong written and verbal communication skills
• Ability to work independently and in collaborative team environments
• Comfort working with complex healthcare data

Preferred Qualifications:

• Experience with AI in healthcare settings
• Experience with digital pathology
• Knowledge of software engineering practices such as version control and CI

Additional Information:

Full-time position with Monday through Friday schedule

Opportunity to work with large-scale clinical and imaging datasets

Focus on research, innovation, and real-world healthcare impact

Pay Type: Salary

Compensation: $68,564 – $80,210 per year

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