
AI Imaging Specialist
14 hours ago
Job Title: Spatial Omics Scientist
Job Description:
We are seeking a motivated PhD candidate to contribute to developing and optimizing deep learning models to analyze digitized H&E slides for cancer classification and spatial mapping. This role is ideal for researchers aiming to apply advanced computational methods to biomedical challenges.
Key Responsibilities:
• Design, develop, and train convolutional neural networks (CNNs) and related ML 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.
Qualifications:
• 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.
Preferred Qualifications:
• Background in cancer histopathology or biomedical image analysis.
• Knowledge of multimodal data integration, including spatial transcriptomics.
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