Postdoc: AI for Medical Imaging & Informatics

St. Jude; Memphis (TN); Vor Ort; USD 60.000 - 90.000; Vollzeit

Zusammenfassung

St. Jude Children's Research Hospital in Memphis seeks a Postdoctoral Research Associate to develop ML/DL models for medical imaging, with a focus on radiology and biomedical informatics.

The role combines cutting-edge AI with translational goals, leveraging large datasets and HPC resources. Ideal candidates have a PhD or MD/PhD, strong Python and DL framework skills, experience with segmentation/detection, and a track record in research.

Qualifikationen

• PhD or MD (or MD/PhD) in Computer Science, Data Science, Biomedical Engineering, Medicine, or a related field.
• Experience with segmentation, detection, and/or quantitative imaging algorithms (2D and/or 3D).
• Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).
• Experience with modern architectures (U-Net variants, transformers, or foundational models).
• Familiarity with Git and collaborative development practices.

Aufgaben

• Design and implement 2D and 3D model architectures for medical imaging problems.
• Apply and adapt LLMs to biomedical and imaging-adjacent tasks, including training and deployment.
• Stay current with AI literature and bring new methods into projects.
• Build scalable data processing, model training, evaluation, and deployment pipelines.
• Develop quantitative imaging methods and biomarker extraction.
• Collaborate with radiologists and engineers to ground research in clinical practice.
• Ensure reproducibility and versioning of experiments.

Kenntnisse

Python

Deep learning

Git

Ausbildung

PhD or MD (or MD/PhD) in a related field

Tools

PyTorch

TensorFlow

Git

Jobbeschreibung

St. Jude Children's Research Hospital in Memphis seeks a Postdoctoral Research Associate to develop ML/DL models for medical imaging, with a focus on radiology and biomedical informatics.

The role combines cutting-edge AI with translational goals, leveraging large datasets and HPC resources. Ideal candidates have a PhD or MD/PhD, strong Python and DL framework skills, experience with segmentation/detection, and a track record in research.