
AI Researcher
7 days ago
We are seeking a motivated PhD candidate interested in machine learning for histopathology image analysis.
The successful applicant will contribute to developing and optimizing deep learning models to analyze digitized H&E slides for cancer classification and spatial mapping.
- 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:
- A PhD in Computer Science, Biomedical Engineering, Data Science, Computational Biology, or a related discipline is required.
- Demonstrated research experience in machine learning, deep learning, or biomedical image analysis is essential.
- Strong programming skills in Python and experience with ML frameworks such as TensorFlow or PyTorch are necessary.
- Familiarity with digital pathology workflows, image preprocessing/augmentation, and annotation tools is desirable.
- The ability to work collaboratively in a multidisciplinary research environment is important.
Benefits:
This is an excellent opportunity to work at the forefront of medical imaging research and contribute to the development of innovative solutions for cancer diagnosis and treatment.
What We Offer:
We offer a dynamic and supportive research environment, opportunities for professional growth and development, and a competitive salary and benefits package.
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