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- 
                Field
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                will perform experiments, develop dose-response models and mechanistic understanding allowing to develop a workflow allowing understanding and awareness amongst different stakeholders. You will be 
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                collaborative labs develop and deploy the latest technology, including sensing, data analytics, modelling, simulation, artificial intelligence, and machine learning, and function as dynamic hubs where innovative 
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                introduced into the PhD trajectory and scientific working. You will alongside the developers of UT’s global crop water model ACEA (Mialyk et al. 2024) and improve the model’s ability to provide recurring 
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                on the development of new antenna and integrated circuit concepts for radar and electromagnetic modelling. The Electromagnetics (EM) and Integrated Circuit (IC) groups are involved as well as the Center for Wireless 
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                , multiphysics simulations, device implementation, and experimental validation. Key responsibilities: Develop theoretical and numerical models of piezoelectric energy harvesters under heavy-load conditions. Design 
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                , and public transport. Options model for additional leave, pension, a bicycle or personal training. Moving allowance (subject to conditions). 30% rule for international employees (if applicable). Pension 
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                on addressing the complexity of the device-software-application-data design space, enabling systematic and efficient exploration using modeling and simulation tools.## Key Responsibilities- Identify and 
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                van Erven. This is what you will do AI and machine learning models keep getting better, but how they make their decisions often remains unclear, because these depend on many incomprehensible model 
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                programmes, large scale science festivals, citizen science and educational initiatives at various levels. EAAS is hiring a total of 20 PhD/postdoc scientists to join the team, and our project/group leaders 
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                , supervised by Dr. Tim van Erven. This is what you will do AI and machine learning models keep getting better, but how they make their decisions often remains unclear, because these depend on many