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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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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
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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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player who contributes positively to collaboration and project success. You also possess: a PhD in Artificial Intelligence, Machine Learning, Computer Science or a related field; at least 3 years of hands
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research institutions. To be considered for the position, you will have: Research experience to PhD level (or equivalent) in a discipline covered by the journal. A passion for science and a desire to learn
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MSCA Doctoral Network position “Electric solar wind sail mission design” We are now looking for two (2) Doctoral Researchers. This PhD topic is part of the “Electric solar wind sail doctors” (E
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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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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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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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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