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Field
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. This PhD aims to address research questions such as how can AI and ML models support the coordinated operation of DERs and smart buildings in the context of limited data? How can AI and ML models increase
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large-scale omics datasets, develop and apply statistical methods and interpretable AI models, and contribute to the identification of biological markers and molecular mechanisms associated with disease
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and the environment. The developed methods will combine wireless sensing with digital map information (e.g. 3D building models), enabling safe autonomous navigation in complex urban environments
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components. You will explore how learning-based methods, such as imitation learning and reinforcement learning, can be integrated with model-based low-level controllers and multimodal sensing to enable contact
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element simulations, blast loading models, propagation of pressure waves in the ground and soil–structure interaction analyses to establish methods for assessing the protective capacity of existing
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and ability to communicate clearly Merits include: Knowledge of LLMs, deep learning, and Python programming Knowledge of power electronics Experience in modelling, simulation, and experimental work In
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described. The project has three main objectives: (1) Use simulation models to make inferences on the role of sex ratio selection on sex chromosome evolution in a different meiotic drive scenarios, (2
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well as presence in extracellular vesicles. A set of human cellular models (also of neuronal type) with endogenous or exogenous expression of polyQ disease-related genes will be used to reveal RNA dysregulation
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Movement Science. Duties of the position Complete the doctoral education until obtaining a doctorate Building and calibrating a multi-compartment environmental fate model to simulate transport, retention and
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, welfare distribution, and operational feasibility. The objective of this PhD project is to develop new knowledge, models, and analytical insights into how future electricity market designs can support the