257 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions in Netherlands
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organizations, Amsterdam Leadership Lab develops evidence-based knowledge and interventions that address real-world organizational challenges. Faculty of Behavioural and Movement Sciences Developing knowledge
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for autonomous systems, healthcare and rehabilitation. You will design and conduct behavioural experiments and develop computational models of multisensory integration and sensorimotor control, using approaches
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integrates molecular biology, genomics, and advanced experimental models to accelerate the development of more effective and less toxic therapies. We are internationally recognized for discovering and
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development. Job requirements We are looking for a highly motivated and independent postdoctoral researcher with a strong interest in multiscale modelling. The candidate should meet the following requirements
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development, various types of leave, and options for sports and cultural activities. You can also tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you
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for developing awareness and engagement with ELSA across ‘use cases’ (UCs) which are specific, real-world examples of technologies and other data-driven approaches related to agricultural data. Within the work
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designing and conducting MR experiments, developing pulse sequences and experimental methods, modeling spin dynamics and relaxation, analyzing data, and interpreting the underlying physical mechanisms
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: Within this international project, TU Delft will develop a machine learning-based forward operator to enable the assimilation of SAR imagery into the crop growth model. You will: Process SAR imagery over
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), are currently being developed to provide more efficient, safer, and more sustainable reactor technologies. One of the bottlenecks for the commercialisation of the technology in the near future is a thorough
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a postdoctoral researcher, you will: Integrate hybrid traffic models and data assimilation methods into a coherent prediction framework. Develop uncertainty quantification methods and explainable and