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better and faster decisions when assessing funding applications, ensuring the efficient and unbiased elimination of poor applications? This question can be addressed through training algorithms on past
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genetics commencing 1 January 2026 or as soon as possible hereafter. Our group and research Laurits Skov’s research group studies the history of humans such as ourselves (homo sapiens), Neanderthals and
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expertise in autonomous marine systems. The research focus will be on development, implementation and verification of novel algorithms for motion planning and control of autonomous underwater vehicles. You
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degradation modes. Evaluating suitable sensor technologies and data sources for acquiring relevant metrics. Developing tools and algorithms to automatically analyse sensor data, assess asset condition, and
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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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algorithm. Design methods: Develop novel control methods for power electronic converters feeding electric machine Simulation: Learn advanced simulation tools such as Ansys to simulate and analyze the effect
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tasks will be to: Genetic engineering of bacteria. Phenotypic characterisation of engineered strains. Teach and supervise BSc and MSc student projects. You must have a two-year master's degree (120 ECTS
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Nordisk. The project will explore the correlation between gene dosage, stability and productivity. Further, different approaches aimed at stabilizing genetic constructs, such as genome integrations
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research initiative MHI aims to establish a potential causal link between the gut microbiome – the combined genetic material of the communities of bacteria and other microbes in the human gut – and the