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and histology datasets. Applying graph neural networks, transformer models and generative AI approaches to study clone-microenvironment interactions. Integrating spatial transcriptomics, single-cell
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acquired across multiple anatomical regions to form a patient-level assessment. This PhD project will investigate novel deep learning methodologies that jointly model anatomical structure and prediction
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: Multimodal Information Retrieval: Developing novel retrieval frameworks that unify heterogeneous scientific data (text, tables, molecular graphs, images, time series) drawn from massive data lakes
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Integreat in Norway! Eight PhD fellowships in machine learning await. Collaborate, innovate, and thrive! PhD Fellowships in Knowledge-Driven Machine Learning in Norway (8 positions) Apply for this job See
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UiO/Anders Lien 9th August 2026 Languages English English English Join Integreat in Norway! Eight PhD fellowships in machine learning await. Collaborate, innovate, and thrive! PhD Fellowships in
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system to track proposals. Evaluate and perform preliminary analysis of the data using graphs, charts or tables to highlight the key points of the research results collected in accordance with the research
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on energy-efficient circuit design and software-hardware co-optimization, with exciting applications in graph-based prediction. What we’re looking for: A PhD in Electrical and Computer Engineering or a
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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(directed acyclic graphs, g-computation, propensity score methods, instrumental variables, and natural experiments), counterfactual mediation analysis in its various forms (natural direct and indirect effects