Doktorand i datoriserad bildbehandling
Core
Developing new methods for image analysis and machine learning to support precision medicine and clinical decision-making for cancer immunotherapy.
Role type
PhD researcher (Doctoral Candidate) in computational image processing
Builds
Interpretable data-driven analysis methods for multimodal microscopy data to predict disease progression and treatment response
Domain
Biomedical research / Deep learning / Computational pathology
Deliverable
production ML models
Required skills
Deep learning frameworks (PyTorch, TensorFlow), Python programming, GPU programming, mathematical modeling, statistics, image processing, computer vision, neural networks
Preferred skills
Graph-based methods and GNNs, fold-and-transformer based networks, explainable AI (XAI), Git version control, LaTeX typesetting, Linux environment, biomedical research interest
Technologies
PyTorch, TensorFlow, Python, Linux, Git, LaTeX
Responsibilities
Conduct independent research on image analysis and machine learning methods for cancer immunotherapy; Integrate structural and molecular analysis in 3D tissue space; Apply analysis methods to high-information multimodal microscopy data; Engage in teaching and administrative work (max 20%)
Seniority
PhD Candidate (Researcher)