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Master's and PhD students. Candidates will be responsible for creating a collaborative work environment within and outside QGG that integrates novel innovative research programs towards the green transition
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. Software or code development, incl. artificial intelligence and machine learning. Automation and robotics, incl. safe human-machine interaction. Serious gaming, incl. AR/VR. Life cycle analysis. You are
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-critical water infrastructure that runs on aging software. When it fails, the impact can be severe: disruption, financial loss, and safety risks. The project delivers practical solutions to make critical
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with an interest in ecological applications. Required qualifications: PhD (or equivalent) in computer science, biology, software engineering, or a related field Strong proficiency in Python, including
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an LLM-assisted software framework for first-principles simulations, thereby gaining extensive experience within scientific software development and AI-driven workflow automation. The work will initially
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dermal atomic force microscope (HS-DAFM) control software and signal processing circuits. These systems are critical for capturing high-quality nanotexture images from skin samples collected across five
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infrastructure that runs on aging software. When it fails, the impact can be severe: disruption, financial loss, and safety risks. The project delivers practical solutions to make critical infrastructure software
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collaboration with local water utilities and software developers Integrate digital urban water twins with data, applying methodologies for data assimilation, parameter estimation, and quantification of model