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work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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materials, (d) Artificial Intelligence (AI) models to predict and control the construction process, (e) a digital twin / information backbone that enables cohesive operation of the design and production
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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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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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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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limited to one year with the possibility of extension. The research assistant position may potentially lead to the opportunity to begin a PhD position based on the candidate’s career stage and wishes. We
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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