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Field
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) years in Computer Science, Data Science, Computational Engineering, Bioinformatics, Computational Social Science, or another highly quantitative field with substantial emphasis on machine learning, deep
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Intelligence & Machine Learning Develop machine learning and AI models to identify, predict and characterise genome instability patterns. Design generative and predictive computational models to infer mutational
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The Research Fellow (RF) will conduct research in the field of coastal dynamics, with a focus on the development and application of machine-learning-enhanced coastal models. The project aims
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the correctness, robustness and reliability of deep neural networks and AI-enabled software systems. Job Responsibilities: Conduct research in adversarial machine learning, AI security and the robustness of deep
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UiO/Anders Lien 16th October 2026 Languages English English English PhD Research Fellow in Machine Learning and Statistics Apply for this job See advertisement About the position Integreat
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methods and deep learning to enable scientific reasoning. Develop software prototypes for automated research workflows that integrate autonomous discovery pipelines with modern deep learning architectures
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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record of publications in reputable peer-reviewed journals in maritime transport, logistics management, machine learning, deep learning, or optimization Proficient in both written and spoken
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research. Key Responsibilities: Develop, implement, and optimize machine learning/deep learning models for digital pathology image analysis Analyze large-scale histopathology, omics, and clinical datasets
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computing environments and GPU computing. Proven experience in weather and climate models development and applications. Experience in machine learning, deep learning, or AI applications for atmospheric