Consultant, Intelligent Medical Image Processing (6 months)

Job Description


Job Responsibilities

Scope of Consultancy Services:
  • Enhance the team’s technology ability on machine learning (ML), deep learning (DL), computer vision (CV) and medical image processing.
  • Provide project service, help to solve the technique issues encountered during the project and instruct on algorithm model improvement.
  • Consultancy on the medical image computer aided diagnosis (CAD) related data augmentation, generalized deep learning model design, medical image analysis etc. industry direction and academic research scope.
  • Bi-weekly meeting with the team.
  • 1st Project Milestone
    • Provide at least 2 technical lectures related to intelligent medical image analysis:
      1. Technology trend on machine learning/deep learning for medical image analysis
      2. A systematic review on data argumentation techniques
    • Offer guidance and advice to the DL/ML algorithm design, which includes:
      1. Generative Adversarial Network (GAN) model design to address data imbalance and sparsity issue for endoscopic image analysis.
      2. Self-Supervised Learning (SSL) methods to solve the problem of low quality and low quantity of data labelling.
      3. Generalized DL model design for endoscopic image analysis.
  • 2nd Project Milestone
    • Provide at least 1 technical lecture related to intelligent medical image analysis:
      1. A systematic review on the self- and semi-supervised learning
    • Review the algorithm models and results, instruct on the performance improvement, which includes:
      1. Lesion detection and early gastric cancer identification in endoscopic image
      2. Endoscopic image anatomical site classification
    • Contribute one innovative idea in the field of AI medical image analysis.


  • Ph.D. Degree in Computer Science or related disciplines
  • 5+ years of experience in ML/DL algorithm research or computer vision related research in the field of medical image analysis.
  • Both industry and academic research experience are highly preferred; can understand the requirement, formulate the problem, and propose innovative solutions addressing the problem effectively
  • Good understanding and appreciation of algorithmic level fine tuning versus system-level performance optimization – various trade-off, parameters, adjustment, and modelling effects etc.
  • Broad knowledge and connection in the community – keep abreast of the state of art of the latest progress, other industry players approach and academic R&D direction.


Interested candidates please send application (quoting Ref. No.) with detailed resume, current and expected salary to Talent Acquisition via email to [email protected]

Only short-listed candidates will be notified. ASTRI reserves the right not to fill the position.

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