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Field
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focuses on the analysis of neuronal networks in the Drosophila brain, and the Hummel team currently consists of postdocs, pre-docs, master students and administrative colleagues who share a common interest
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development. This entitlement, from the Concordat to Support the Career Development of Researchers , applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP
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Subject area: Drug Discovery, Sustainability, Laboratory Automation, Microfluidics, Machine Learning Overview: This highly interdisciplinary 4-year funded PhD studentship will contribute to cutting
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expand current technology to include automated live analysis, integrating machine learning algorithms capable of interpreting the complex behavioural patterns of mussels in response to environmental stress
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to address urgent challenges in animal conservation and welfare. However, existing technologies have mostly been developed for use in controlled laboratory settings and are often unsuitable for field
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can personalize and automate home environments to improve comfort for residents, including temperature control, lighting, and air quality. Objective 3: Assess the role of digital twin technology in
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integration, and real-time optimisation, the project will ultimately help develop an adaptive system that helps pilots and controllers make smarter decisions mid-flight. The research will advance through three
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robotic automation to identify and optimise lead compounds. This approach will serve as a test case for a generalisable platform for rapid, structure-guided antiviral discovery. Approach and Methods
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engineering applications, and their tight integration with planning and control (e.g., task-and-motion planning, differentiable planning, or Reinforcement Learning (RL) with safety constraints). There will be
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap