Advanced Biomedical Image Analyst

2 days ago

Delhi, Delhi, India beBeeBiomedical Full time ₹ 6,00,000 - ₹ 8,00,000

Job Title: Advanced Biomedical Image Analyst

Experience: Freshers

Location: Delhi

Job Description:

We are seeking a motivated PhD candidate interested in machine learning for histopathology image analysis. The candidate will contribute to developing and optimizing deep learning models to analyze digitized H&E slides for cancer classification and spatial mapping. This role is well-suited for researchers aiming to apply advanced computational methods to biomedical challenges. We offer a collaborative research environment where you can apply your skills to real-world problems and advance the field of biomedical image analysis.

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.

• Document research findings and contribute to publications in peer-reviewed journals.

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 (e.g., publications, thesis projects, or conference presentations).

• 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:

• Background in cancer histopathology or biomedical image analysis.

• Knowledge of multimodal data integration, including spatial transcriptomics.

This is an excellent opportunity to join a dynamic team of researchers and contribute to advancing the field of biomedical image analysis. If you are passionate about applying machine learning to real-world problems and have a strong background in computer science and biomedical engineering, we encourage you to apply.

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