2,400 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" PhD positions
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develop a new generation of hybrid models combining large-scale machine learning with physical knowledge to represent interactions between mobile robots and their environment. The research will address
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Global Change Group at Wageningen University and Research invites applications for a PhD position (4 years) in “Modelling non-CO2 greenhouse gas emissions from agriculture” starting in September 2026
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-driven optical spikes, enabling sensing systems with unprecedented speed and energy efficiency. A central objective of the project is to develop highly sensitive photodetector neurons by combining resonant
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Power-to-X systems. You will drive the development of system-level digital-twin and optimization methodologies, integrating electrolyzer models with renewable generation, power conversion, energy and
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statistical approaches to characterise disease trajectories, develop risk prediction models, and identify factors associated with differential treatment outcomes. The findings will improve understanding of long
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Are you intrigued by the potential of light-driven chemistry to create sustainable, bio-based polymers? Are you passionate about developing innovative recycling technologies that support a more
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learning from demonstrations and generalisation to unfamiliar tasks, objects or environments. World models and planning Develop models that predict how the physical world responds to actions, supporting
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to develop and implement state estimation algorithms, such as Kalman filters and observers, for real-time applications. Proficiency in MATLAB and Simulink for modelling, simulation, and validation using
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-timescale optimization, and integrated Power-to-X systems. You will drive the development of system-level digital-twin and optimization methodologies, integrating electrolyzer models with renewable generation
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largely undeveloped. Addressing this challenge will be the central objective of your PhD research. Responsibilities and qualifications You will develop a physics-based modelling framework for bearingless