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application! We are now looking for a PhD student in infrainformatics with focus on semantic and goal-oriented communication specialized on cloud-assisted artificial intelligence and control systems. Your work
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providing interdisciplinary neuroscience training and professional development. Where to apply Website https://www.academictransfer.com/en/jobs/357256/phd-student-biotype-based-perso… Requirements Specific
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to convert model state variables (e.g., LAI, canopy temperature) into synthetic observations Evaluate the performance of the data assimilation framework in controlled experiments and evaluate its potential
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dedicated cleanroom area supports the assembly and integration of flight hardware, ensuring high reliability and adherence to space standards. Adjacent to the electronics lab, the Space Technology Testing
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of the data assimilation framework in controlled experiments and evaluate its potential for spaceborne remote sensing and landscape-scale applications Improve simulation accuracy for key ecosystem variables
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the broader framework of Embodied AI. The goal is to integrate physical models with deep learning to create interpretable, data-driven observers that enable physically grounded perception and control for robust
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are later analysed in detail in our laboratories in Yerseke. Laboratory work can includes working with live species, running experiments from small-scale controlled studies, to larger experiments in flumes
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– and building on recent advances in foundation models, neural model predictive control, and robotic world models – this PhD project will investigate principles and mechanisms for a shared autonomy
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sector to study how intelligence emerges from the interaction between body, computation, and environment, across flying, ground, and aquatic robot configurations. Our mission is to chart a generalizable
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apply with no application fee during Free Application Week, October 6–10, 2025.👉 Learn more and apply here: https://go.ua.edu/4g4YUyJOur faculty are advancing knowledge and innovation across four dynamic