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construction of optical diffraction tomography or quantitative phase microscopy systems. Experience in the development of fluorescence-based super-resolution microscopy methods such as structured illumination
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criteria Experience with large C++ code bases Experience with MLIR and/or LLVM frameworks Experience with Precision Tuning and/or other approximate computing methods Experience with one or more heterogeneity
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in-depth qualitative analyses but also mixed-methods approaches, possibly enabled by emerging AI-enhanced techniques. The PhD project should overall contribute to a better understanding collaborative
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sequencing-based methods for immunological characterization. Fluent oral and written communication skills in English. Preferred selection criteria A strong background in imaging techniques and proteomics
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system stability. To address these challenges, predictive maintenance (PdM) techniques have emerged, leveraging real-time condition monitoring, fault diagnostics, and remaining useful life (RUL) estimation
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interdisciplinary center with joint efforts in theory, computer simulations and experiments, both in fundamental and in more applied directions. The center works to advance the understanding of porous media by
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knowledge of the relevant scholarship in International Relations (see above). Knowledge of qualitative research methods is required. The project language is English and the applicants should have an excellent
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the so-called multimodal turn, including collaborative and reciprocal research, experimentation with storytelling, expansion of methods beyond traditional text-based ethnography, and evolving public roles
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in quantitative methods (reflected in courses and/or research experience) Proficiency in R, Python, or similar programming languages (or strong skills in another statistics software) Knowledge about
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ecologies. Such examinations may require in-depth qualitative analyses but also mixed-methods approaches, possibly enabled by emerging AI-enhanced techniques. The PhD project should overall contribute to a