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for establishing properties of quantum programs - Reduction methods and metrics for quantum systems - Decision diagrams for efficient analysis and simulation of distributed quantum programs - Statistical model
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models and reinforcement learning models for 3D graphs of materials to explore vast inorganic chemical spaces and design synthesizable energy materials. You will couple such models with physics simulation
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Motivated Language Model Detection”) and an NNF: Ascending Data Science Investigator project (“LM2-SEC: Linguistically Motivated Language Model Security”). Your work tasks As a PhD student, you will conduct
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-on experimentation with advanced digital fabrication, numerical modelling, material testing, and process optimization. You will work on the fabrication and mechanical characterization of composite specimens with
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measurement techniques/ sensors. Experience with system modelling and simulation (e.g., TRNSYS, Python, or similar tools). System and control engineering (e.g. digital twins, model predictive control) –pre
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. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process & microstructure with
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, processing video data, and applying AI models to improve efficiency in population and behavioral analyses. Fieldwork will be combined with statistical and spatial analysis using RStudio and GIS tools. In
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surgical robots across various surgical applications, using techniques such as advanced sensing, AI-based and reinforcement learning (RL)-based control, and soft continuum robot simulation. The starting date
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is expected to have a profound knowledge on most of the following topics: Robot control Deep Learning Medical imaging Preferably, the candidate has experience with: Robotic simulation tools Medical
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and reinforcement learning (RL)-based control, and soft continuum robot simulation. The starting date is expected to be February 15, 2025, or as soon as possible thereafter and will be agreed with