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inviting applications for a PhD Student (f/m/x) for the project Theory and Algorithms for Structure Determination from Single Molecule X-Ray Scattering Images Project description Single molecule X-ray
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include placing machine vision cameras, performing laboratory trials of closed-loop plant care for example with a gantry robot, comparing day and night imaging, and developing and evaluating automated and
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number of techniques routinely used in the lab including histology, confocal microscopy and image processing. Prior expertise in cell culture, image analysis and coding would be highly appreciated. Part of
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Swinburne University of Technology Swinburne Horizon 2025 draws upon our understanding of future challenges. With this new strategic plan, we choose to build Swinburne as the prototype of a new and different
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Research Assistant Professor, Research Associate Professor, Assistant Professor, Associate Professor
, an active doctoral studies program, and state-of-the-art instrumentation. Onsite facilities include those for flow cytometry, confocal microscopy, live animal imaging, laser capture microdissection, phosphor
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unrelated to their own. They attend practical courses in novel technologies (live imaging, genomics, proteomics, etc.) and soft skills courses (scientific writing, presentation skills, intellectual property
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interactions, as well as establishing fluorescence lifetime imaging microscopy (FLIM) approaches and analysis pipelines to perform non-destructive monitoring of neuronal function, DAMs, and multiplexing
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thermochemical TES. Your main supervisor will be Prof Adriano Sciacovelli and you will join the Thermal Energy Section at DTU Construct. Your work will contribute to a paradigm shift in how complex TES systems
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methodologies, including quantitative, qualitative, and mixed methods. Innovation: Noble thinking and ability to innovate a new prototype to solve industry gaps in cyber security. Analytical skills: Problem
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data