Postdoctoral Researcher

Project Overview

1. AI Model Development & Testing

• Assist in developing machine learning and deep learning models for medical imaging analysis.
• Implement and fine-tune models using PyTorch, TensorFlow, or related frameworks.
• Run experiments, perform hyperparameter tuning, and maintain organized experiment logs.

2. Medical Imaging Data Management

• Support data preprocessing, annotation preparation, and dataset organization.
• Handle CT, MRI, PET, and histopathology images, ensuring proper anonymization and compliance with ethical guidelines.
• Collaborate with clinicians to understand imaging structures and diagnostic targets.

3. Explainable AI Implementation

• Integrate XAI methods (e.g., Grad-CAM, Guided Backprop, SHAP) into the system.
• Generate and interpret visual explanations for model outputs.

4. System Prototyping & Software Development

• Contribute to the development of the AI Pathologist prototype, including UI/UX, backend integration, and workflow automation.
• Support deployment of models using Docker, APIs, or cloud environments.

5. Documentation & Reporting

• Prepare technical documentation, coding standards, and user guides.
• Assist in preparing project reports, research papers, and meeting presentations.

6. Collaboration

• Work closely with radiologists, pathologists, and clinicians to understand requirements and validate outputs.
• Attend project meetings and provide weekly progress updates.

Education

• Master degree or PhD in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, Biomedical Engineering, or a related field.

Technical Skills

• Experience with Python and machine learning libraries (PyTorch, TensorFlow, scikit-learn).
• Understanding of deep learning, CNNs, Capsule Networks, and image processing fundamentals.
• Basic knowledge of handling medical images (e.g., DICOM).
• Familiarity with version control (Git/GitHub).

Soft Skills

• Strong analytical and problem-solving skills.
• Good communication and teamwork ability.
• Ability to document work clearly and follow research procedures.

Technical Skills

• Experience with:
• 3D imaging models (3D CNNs, UNet variants, VNet)
• Explainable AI tools (Grad-CAM, LIME, SHAP)
• Medical imaging workflows, PACS systems
• Docker, APIs, and model deployment
• Cloud platforms (AWS, Azure, GCP)
• Experience working on healthcare-related AI projects.

Clinical Collaboration

• Previous collaboration with hospitals or medical researchers.
• Understanding of radiology/pathology imaging interpretation.

Other Advantages

• Publications or strong project portfolio in computer vision/medical AI.
• Experience with data annotation tools.
• Knowledge of cybersecurity and data governance in healthcare.