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.

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