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foundations of medical deep learning. The project focuses on novel self-supervised objectives, information geometry, mitigating representation bias for rare pathological findings, and building next-generation
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intelligence, data science, medical physics, neuroimaging, bioengineering, or related disciplines, accompanied by accredited training in machine learning, deep learning, or medical image analysis. Experience: A
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with deep-learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum, the deadliest malaria parasite species (read [1] to learn more about the ideas behind
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them using state-of-the-art bioinformatics approaches, increasingly incorporating AI and deep learning (see, e.g., Sarropoulos et al., Science 2026). This work has provided insights into the origins and
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data science, biomedical engineering, technical medicine, or a related field. You should have strong programming skills (Python, PyTorch), deep learning knowledge (multimodal learning, longitudinal
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Learning and software engineering with at least 3-5 years of research experience (including PhD training) in related fields. Proven track record in research and development of cybersecurity and/or Deep
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, Atmospheric Science, LSTMs, VAEs, PyTorch, TensorFlow, NumPy, pandas, scikit-learn, spatio-temporal datasets Additional Information Eligibility criteria Mandatory: *A PhD in Data Science, Artificial
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traditional custodians of the land, sea and waters of the areas upon which we live and work. We recognise their valuable contributions and deep connection to country and pay respect to Elders past and present
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/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 - the Norwegian
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theoretical advances into practical insight and tools that can support analysis, design and decision-making for AI-enabled space systems, thereby bridging the emerging scientific theory of deep learning with