Lead Deep Learning Researcher

1 day ago


Surat, Gujarat, India beBeeMachineLearning Full time ₹ 6,00,000 - ₹ 10,00,000

Job Opportunity

We are seeking a motivated PhD candidate to develop and optimize deep learning models for analyzing digitized histology images.

This role is well-suited for researchers aiming to apply advanced computational methods to biomedical challenges, particularly in the area of cancer classification and spatial mapping.

Key Responsibilities:

  • Design, develop, and train convolutional neural networks (CNNs) and related machine learning models on H&E-stained histology images.
  • Use and extend tools such as QuPath for cell annotations, segmentation models, and dataset curation.
  • Preprocess, annotate, and manage large image datasets to support model training and validation.
  • Collaborate with cross-disciplinary teams to integrate image-based predictions with molecular and clinical data.
  • Analyze model performance and contribute to improving accuracy, efficiency, and robustness.
  • Document research findings and contribute to publications in peer-reviewed journals.

Requirements:

  • PhD in Computer Science, Biomedical Engineering, Data Science, Computational Biology, or a related discipline.
  • Demonstrated research experience in machine learning, deep learning, or biomedical image analysis.
  • Strong programming skills in Python and experience with ML frameworks such as TensorFlow or PyTorch.
  • Familiarity with digital pathology workflows, image preprocessing/augmentation, and annotation tools.
  • Ability to work collaboratively in a multidisciplinary research environment.

Preferred Qualifications:

  • Background in cancer histopathology or biomedical image analysis.
  • Knowledge of multimodal data integration, including spatial transcriptomics.


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