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Infrastructure? No Offer Description Work group: PGI-15 - Neuromorphic Software Eco System Area of research: Promotion Job description: Your Job: The conventional, manual co-design of algorithms and hardware is
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in a broad and impartial manner. The work can draw on algorithms from the recent work of the process design management team. Several generative algorithms have been produced: using evolutionary
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evolutionary algorithms for shape-optimisation problems. Key responsibilities Assist in relevant teaching activities; Perform PhD research on one of the above topics and publish in top venues; Collaborate
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tailored multi-objective evolutionary algorithms for shape-optimisation problems. Key responsibilities Assist in relevant teaching activities; Perform PhD research on one of the above topics and publish in
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development and application of novel algorithms and machine learning/AI techniques for extracting insights from biological data sets (genomics, proteomics, imaging, neuroscience), and related areas
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of algorithms and models to realistically simulate forest ecosystem dynamics under varying conditions of land use change, forest and land management, climate variability, and other environmental stressors
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stability of swarm behaviour, and validate novel control strategies that quickly adapt to rapid changes in supply/demand. New effective market, contracting, and algorithmic mechanisms are needed to be derived
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, prove the convergence and stability of swarm behaviour, and validate novel control strategies that quickly adapt to rapid changes in supply/demand. New effective market, contracting, and algorithmic
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minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
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industry partners. Design, implement, and validate advanced reinforcement learning models. Utilize reinforcement learning and evolutionary algorithms to discover new chemical materials. Publish and present