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development, electronics and the development of data analysis pipelines incorporating machine learning. In collaboration with biological partner groups, the developed system will be benchmarked and applied
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innovations and the biological discoveries they enable Your profile You have: a PhD in engineering, computer science, mathematics or a related field a strong background and proven experience in machine learning
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apply advanced signal data analysis approaches, including machine learning and AI-based modelling Quantify early brain maturation markers and relate them to visuomotor developmental outcomes Work closely
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-computer interfaces, audio signals for keyword spotting and artificial cochleas, and tactile signals for robot perception. Various types of bio-inspired mechanisms have been investigated in recent years
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to candidates who combine research expertise in the fields of business analytics, machine learning for business decision-making and AI-driven process optimisation with expertise in the impact, ethical
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from empirical to machine learning approaches Experience in collaborating effectively with chemists and biologists Demonstrated track record of leading early hit finding and hit-to-lead programs
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engineering stimulated by recent developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with
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developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with the running infrastructures. Using
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-order modelling, surrogate models, and machine-learning methods such as neural networks. Control design for flexible reactor operation. Develop advanced control strategies that enable safe and efficient
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-scale nature, complexity, and heterogeneity of 6G networks, we use tools such as artificial intelligence/machine learning, quantum computing, graph theory, graph-signal processing, and convex/non-convex