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Field
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diffusion techniques to design materials with targeted optical properties, scaling to large systems through efficient representations and GPU parallelization. We will also create multi-fidelity predictive
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research role. We encourage all potential applicants to think about potential proposals for parallel individual projects which may complement these two research projects, and we will work with you to refine
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knowledge and tools to equip local decisionmakers to better deal with conflicting values in parallel transitions and requires an interest in both theory development and engagement with practice. The PhD
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separate and parallel application must also be submitted via the TU Delft's vacancy and talent recruitment portal. Additional comments PhD enrolment The selected applicant will be enrolled into the Ph.D
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information through parallel channels—manual signs, spatial grammar, facial expressions—operating simultaneously in 3D space, presenting unique computational challenges for cross-modal alignment. The project
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to generate the necessary knowledge and tools to equip local decisionmakers to better deal with conflicting values in parallel transitions and requires an interest in both theory development and engagement with
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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights
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need to be enrolled in one of the EPFL doctoral school programs. This is a separate application process that you can start in parallel. We suggest that you apply to the Doctoral Program in Mechanics
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stakeholders. This multidisciplinary PhD project aims to generate the necessary knowledge and tools to equip local decisionmakers to better deal with conflicting values in parallel transitions and requires
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2: A separate and parallel application must be also submitted for this PhD position on DTU’s List of Vacant Positions once this position is announced at DTU’s List. Application sent before 1st