Artificial Intelligence Research Scientist

24 hours ago

Ajmer, Rajasthan, India beBeeMachineLearning Full time ₹ 10,00,000 - ₹ 15,00,000
Job Title: Artificial Intelligence Research Scientist

We are seeking a motivated PhD candidate with expertise in artificial intelligence and machine learning for histopathology image analysis.

This role is ideal for researchers aiming to apply advanced computational methods to biomedical challenges, driving innovation and discovery in the field.

  • Design, develop, and train convolutional neural networks (CNNs) and related AI models on H&E-stained histology images to achieve precision and accuracy.
  • Leverage and extend tools such as QuPath for cell annotations, segmentation models, and dataset curation to streamline workflows and enhance productivity.
  • Preprocess, annotate, and manage large image datasets to support model training and validation, ensuring data quality and consistency.
  • Collaborate with cross-disciplinary teams to integrate image-based predictions with molecular and clinical data, fostering a culture of collaboration and knowledge sharing.
  • Analyze model performance and contribute to improving accuracy, efficiency, and robustness, applying statistical techniques and experimental design.
  • Document research findings and contribute to publications in peer-reviewed journals, showcasing expertise and contributing to the scientific community.

Requirements:

  • PhD in Computer Science, Biomedical Engineering, Data Science, Computational Biology, or a related discipline, demonstrating a strong foundation in AI and ML principles.
  • Demonstrated research experience in AI, ML, deep learning, or biomedical image analysis, showcasing expertise and accomplishments.
  • Strong programming skills in Python and experience with AI frameworks such as TensorFlow or PyTorch, enabling efficient development and deployment of models.
  • Familiarity with digital pathology workflows, image preprocessing/augmentation, and annotation tools, ensuring seamless integration and effective utilization.

Preferred Qualifications:

  • Background in cancer histopathology or biomedical image analysis, providing a unique perspective and expertise.
  • Knowledge of multimodal data integration, including spatial transcriptomics, driving innovation and advancing research capabilities.

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