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naukri

Postdoctoral Researcher

Heriot Watt University
United Arab Emirates, UAE
Senior
1 months ago
PythonPyTorchTensorFlowscikit learnDeep LearningCNNs
Free

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Project Overview

  • The AI Pathologist project is an interdisciplinary initiative aimed at developing an advanced AI driven diagnostic system using 3D medical imaging modalities (CT, MRI, PET) and explainable AI (XAI) techniques to support medical professionals in improving diagnostic accuracy, reducing workload, and e
  • The Postdoc Researcher will play a key role in implementing system prototypes, managing data pipelines, and supporting the development and validation of AI models in collaboration with clinicians and engineers.

Key Responsibilities

  • 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.
  • 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.
  • Integrate XAI methods (e.g., Grad CAM, Guided Backprop, SHAP) into the system.
  • Generate and interpret visual explanations for model outputs.
  • 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.
  • Prepare technical documentation, coding standards, and user guides.
  • Assist in preparing project reports, research papers, and meeting presentations.

Minimum Requirements (Essential)

  • Master degree or PhD in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, Biomedical Engineering, or a related field.
  • 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).
  • Strong analytical and problem solving skills.
  • Good communication and teamwork ability.
  • Ability to document work clearly and follow research procedures.

Preferred Requirements (Highly Desirable)

  • Experience with 3D imaging models (3D CNNs, UNet variants, VNet).
  • Experience with Explainable AI tools (Grad CAM, LIME, SHAP).
  • Experience with medical imaging workflows, PACS systems.
  • Experience with Docker, APIs, and model deployment.
  • Experience with cloud platforms (AWS, Azure, GCP).
  • Experience working on healthcare related AI projects.
  • Previous collaboration with hospitals or medical researchers.
  • Understanding of radiology/pathology imaging interpretation.
  • Publications or strong project portfolio in computer vision/medical AI.
  • Experience with data annotation tools.
  • Knowledge of cybersecurity and data governance in healthcare.

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