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Field
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
of simulation, optimization, and policy modelling. You will also connect with TU Delft's strong internal network on climate action, particularly through the Climate Action Programme and its Climate Governance
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redesigning the drivetrain of bicycles and handcycles. As a PhD candidate, you will use musculoskeletal modeling and experimental testing to explore how muscles and limbs should move to deliver maximal power
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sciences, economics and regulation. Job description The project of the PhD student based at CWI in Amsterdam will focus on techno-economic models (and in particular multi-agent modeling) of energy exchange
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models. In these models, future water use is typically based on the projections of integrated assessment models. However, it is likely that societies will formulate response strategies to imminent water
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statistical models for the dynamic prediction of survival outcomes in complex longitudinal studies” under the supervision of dr. Mirko Signorelli. What you will do The Mathematical Institute of Leiden
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, stability, safety, and usability under clinically relevant constraints. Perform ex vivo evaluations using soft-tissue models to simulate gastrointestinal navigation and refine the system’s interface and
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, device modelling/simulation aspects of new tunnelling devices. By using dedicated electrical dc and RF measurement equipment within our measurement & test centre, you will develop and carefully analyse
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–specific ways, and their downstream biological effects remain poorly understood. This project tackles this fundamental gap — by building computational models that simulate what goes wrong in the brain, one
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elements/agents, adjusting expectations, mechanisms of contagion dynamics, feedback loops, and non-linear tipping of system dynamics. The SPHINX research program aims to fundamentally advance simulation
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networks are built on the same geometric foundation, namely Euclidean geometry. This choice however leads to fundamental limitations that cannot be overcome with bigger models and larger datasets. A critical