Machine Learning Engineer - H&E Staining

Job Title : H&E Image Analysis Scientist / Machine Learning Engineer- Spatial Omics (PhD) Experience : FreshersLocation : DelhiJob Description : We are seeking a motivated PhD candidate interested in machine learning for histopathologyimage analysis. The candidate will contribute to developing and optimizing deep learningmodels to analyze digitized H&E slides for cancer classification and spatial mapping. Thisrole is well-suited for researchers aiming to apply advanced computational methods tobiomedical challenges.Responsibilities :

• Design, develop, and train convolutional neural networks (CNNs) and related MLmodels on H&E-stained histology images.
• Use and extend tools such as QuPath for cell annotations, segmentation models, anddataset curation.
• Preprocess, annotate, and manage large image datasets to support model trainingand validation.
• Collaborate with cross-disciplinary teams to integrate image-based predictions withmolecular and clinical data.
• Analyze model performance and contribute to improving accuracy, efficiency, androbustness.
• Document research findings and contribute to publications in peer-reviewed journals.Qualifications :
• PhD in Computer Science, Biomedical Engineering, Data Science, ComputationalBiology, or a related discipline.
• Demonstrated research experience in machine learning, deep learning, or biomedicalimage analysis (e.g., publications, thesis projects, or conference presentations).
• Strong programming skills in Python and experience with ML frameworks such asTensorFlow or PyTorch.
• Familiarity with digital pathology workflows, image preprocessing / augmentation, andannotation tools.
• Ability to work collaboratively in a multidisciplinary research environment.Preferred :
• Background in cancer histopathology or biomedical image analysis.
• Knowledge of multimodal data integration, including spatial transcriptomics.