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with experts to automate diagnostic assays, leading to cost-effective, easy to use tests Work closely with AMR, Informatic and Machine Learning colleagues ensure the tests provide accurate pathogen ID
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: Advanced deep learning architectures Mathematical foundations of machine
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funding and lead research projects, conduct innovative data-driven research in life sciences using computational modelling, machine learning and advanced analytics, publish in high-impact international
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informatics, molecular simulation, computer-aided molecular design, and chemically aware machine learning. Our mission is to enable a deeper interrogation of biology through the integration of chemistry
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Solid programming skills, e.g., Python, machine learning frameworks, data analysis tools Experience with social media research or large language models is an advantage Strong analytical thinking and
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, and machine learning. The environment at GBI will allow researchers to undertake ambitious, long-term, collaborative research, and we will actively support the translation of research to commercial
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Research Assistant in Physical Computing and Wearables at the Department of Computer Science, Aar...
research is at the cutting edge of Human-Computer Interaction (HCI), personal fabrication, and physical user interfaces. As a research assistant, you will support our research team on implementing a novel
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has a passion for continuing to push the boundaries of our understanding. Candidates who demonstrate responsibility, initiative, and a strong drive to learn and succeed in a collaborative environment
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of this programme. The profile PhD in computer vision, computational biology, physics or a related discipline Demonstrated expertise in image analysis and working with large-scale imaging datasets Strong expertise in
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of cutting-edge tools, models, and strategies to understand and engineer immune systems for translational medicine. Candidates may use integrative approaches that combine immunogenomics, machine learning