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models optimised with evolutionary algorithms to address combinatorial optimisation in model design and the noisy nature of climate data. The Doctoral Researcher will receive on-the-job training in machine
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mission. You will: Help collate data resources relevant to suicide and self-harm. Develop new machine learning methodologies (from artificial neural networks, decision trees, evolutionary algorithms and
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Machine Learning. Work plan: Review of the state of the art on Evolutionary Algorithms and image tampering detection; Implementation of an evolutionary algorithm for image tampering detection
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. Develop new machine learning methodologies (from artificial neural networks, decision trees, evolutionary algorithms and others) compatible with epidemiology. Produce a digital twin for national suicide and
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Assessment Systems: Toward Trustworthy AI for Complex Educational Evaluation Image and Video Analysis Using Machine Learning Algorithms Mathematical and Computational Neuroscience, from neural data and network
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range of disciplines, including evolutionary biology, ecology, computational biology, genetics, and comparative genomics. The build-up of biodiversity gradients from spatial diversification dynamics 1
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biology and bioinformatics, as well as in Machine Learning (including Large Language Models). Good understanding of evolutionary and molecular biology concepts, and good statistical (data analysis) and
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Your Job: The conventional, manual co-design of algorithms and hardware is slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is
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combines computational analysis, evolutionary experiments and genomics, to gain a deep insight into how cancers adapt. Research projects in the Cresswell group are supported by the Austrian Science Fund (FWF
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combines computational analysis, evolutionary experiments and genomics, to gain a deep insight into how cancers adapt. Research projects in the Cresswell group are supported by the Austrian Science Fund (FWF