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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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, including: Robot Learning: Creating algorithms that empower robots to learn autonomously from interactions and adjust to new tasks. Manipulation: Enhancing techniques for precise and adaptable object handling
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position is ideally suited to candidates with a strong interest in root adaptations and molecular cell biology. Applicants must be highly motivated and self-driven, with a PhD in molecular biology or a
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indicators and strategies for resilient wetland ecosystems, supporting adaptive management and evidence-based restoration practices. We expect that you will be an important part of the research environment and
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chemistry approaches. - develop functional polymer materials through macromolecular engineering and self-assembly, particularly in the fields of renewable materials, health, and energy - establish lasting
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through other channels. Person Specification: PhD in a discipline with a quantitative background, including statistics, data science, health science, epidemiology or a related areas. Experience in data
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or related areas with research experience on self-adaptation techniques to enhance the efficiency of machine learning based systems. More in detail, a key requirement for eligibility is provable
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indicators and strategies for resilient wetland ecosystems, supporting adaptive management and evidence-based restoration practices. We expect that you will be an important part of the research environment and
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water and food systems. About IsoTrace: Within the framework of the IsoTrace project, our team aims to rethink and adapt research, development, innovation and training to new paradigms to meet the future
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effective lines of communication with all team members The candidate should have a PhD in molecular or cell biology, or a closely related discipline, or equivalent research, industrial or commercial