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, with a creative approach to overcoming obstacles; skilled in practical lab work, particularly in plant biology and microbiology, and have demonstrated experience with bioinformatics and/or machine
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networks, or network science, and relevant background knowledge on methods in machine learning and AI. The successful candidate will focus on innovating the field of network analysis with AI methods
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(+/–) applied to the electrodes can be optimised in a machine-learning approach to optimise the gel morphology and the embedded stimuli-transduction pathways towards the targeted mechanical behaviour. Departing
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. Research methods include computational modelling, brain imaging (fMRI), machine learning, behavioural methods, and other techniques. Virtually everything we sense, think and do is uncertain. For instance
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in open fields, while also embracing data science, smart electronics/devices, computer programming as central to your work? Do you want to contribute to creating future-proof regenerative agricultural
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inventory, a major incentive for the project is the application and adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases
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science, human technology interaction, and machine learning. You will be working at the Human Media Interaction group in which computer science meets social science to investigate, design, and evaluate
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. Through our bachelor’s and master’s degrees, Professional Learning & Development programmes, and interdisciplinary research themes – including Emerging Technologies & Societal Transformations, Resilience
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Science, Data Science, Artificial Intelligence or a related technical field. Experience and knowledgeable in AI techniques (e.g., machine learning, deep learning, predictive analytics) and data-driven approaches
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adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases and in particular the complications encountered in photometric