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conditions, helping to improve design, control, performance, and reliability. What you would be doing: You will focus on developing nonlinear dynamic models of fuel cell electrochemistry and on identifying
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for individuals, organizations or society. You will be part of the SAIL research group, whose research activities focus on AI-based modeling of complex systems, uncertainty management in deep learning, visual
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design within an active, growing translational research program. This is an unusually opportune time to join the lab: the IBC work sits at the leading edge of a paradigm shift in how recurrent UTI is
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learning models (e.g., multimodal AI, large language/world models) with specific finetuning for ELEVATE; designing geographically context-sensitive urban design recommendations that promote active mobility
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outputs. The research methods will include experiment design, software implementation, running deep learning experiments on high-performance computing infrastructure, and evaluation using objective metrics
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working towards a shared goal. You will be responsible for the design and pilot testing of machine learning-based automated ultrasound video analysis models that incorporate temporal reasoning. The research
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, is under threat from growing reliance on artificial intelligence (AI) technology. While designed to assist, AI recommendations may inadvertently impede cognitive reasoning and steer decision-making
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— developed within the project. This is a fixed-term appointment for 18 months from the 1st of September 2026. Your priorities will include: Designing, expressing, and purifying recombinant proteins (including
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dynamic research team focused on the design, synthesis and characterisation of advanced polymeric materials. The successful candidate will undertake cutting-edge research, contribute to high-impact
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assignments, and mentoring students on technical projects. System Design: Build and maintain immersive prototypes that combine real-time physics with modern AI models to support learning and communication