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Role Description
This role involves combining advanced statistical methods, deep learning, and high-performance computing to extract insights from complex datasets—particularly in medical imaging and computational pathology.
• Design and deploy deep learning and transformer-based models tailored for pathology applications.
• Fine-tune large-scale AI and foundation models for clinical use cases.
• Optimize self-supervised and few-shot learning approaches for digital pathology.
• Translate research into production-ready AI tools used in healthcare environments.
• Partner closely with clinicians and computational pathologists to ensure clinical integration.
• Lead and contribute to high-impact publications in top AI and medical journals.
• Mentor junior researchers, engineers, and postdoctoral fellows on technical direction and execution.
• Support cross-functional initiatives to align AI development with healthcare delivery.
• Drive the adoption of scalable AI solutions that meet clinical performance and reliability standards.
Qualifications
• PhD or equivalent experience in Computer Science, Machine Learning, Computational Biology, or related field.
• 3+ years applying deep learning to real-world problems, ideally in medical imaging or healthcare AI.
• Proficient in PyTorch and distributed/multinode training environments.
• Proven experience with model deployment in high-stakes environments.
• Knowledge of medical imaging, histopathology, and genomics preferred.
Requirements
• Strong programming expertise in Python, bash, and CUDA.
• Experience with cloud platforms (AWS, GCP), HPC environments (e.g., SLURM), and infrastructure as code (Terraform).
• Familiarity with containerization tools like Docker and Kubernetes.
• Ability to balance academic rigor with practical deployment in healthcare systems.
Benefits
• Compensation Philosophy
• Pay Range: $148,100.00 - $244,400.00
• FSLA Status: Exempt
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