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-throughput screening workflows and preparing samples for metabolomic analysis. Skills in quantitative image analysis, data processing pipelines, and introductory computational modelling. Competence in
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Postdoctoral researcher (M/F), synthesis of crystal phase heterostructures by Molecular Beam Epitaxy
processing and analysis of TEM images (segmentation, extraction of morphological parameters). Modeling of growth and phase transitions (nucleation kinetics, diffusion mechanisms, droplet stability). Optical
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research by managing imaging data processes, supporting image analysis preparation, and ensuring research-ready datasets for ongoing and future studies. Essential Functions Coordinate imaging workflow
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background in Earth Sciences or another appropriate field. You will work on the project “Nanoscale Rock Magnetism and Magnetic Imaging”. Your job This study is part of the ERC Consolidator project SPARK, which
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equipment and devices; performs computer acquisitions and analysis as required; manages imaging datasets (e.g., transfer, archive, and retrieval); maintains all necessary records and reports in a correct
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to diagnose and troubleshoot problems with clinical photographic and digital imaging equipment. Working knowledge of Microsoft Windows operating environment. Well-developed computer skills. 4. Ability to assist
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energy transfer, developing and employing computer simulations, laboratory experiments, and field analyses. Our aim is to gain fundamental insights and develop sustainable technologies to address societal
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collaboration, we are building a high-throughput single-cell analysis platform that combines microfluidics, advanced imaging and AI-based analysis to study gut microbial consortia. You will drive the development
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documented experience in computer vision, where the PhD project was fully or substantially method-focused on computer vision and/or AI-based image or video analysis have very strong knowledge of machine
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imaging of subfield scattering targets." Optics Letters 41(21): 4959-4962, 2016. http://dx.doi.org/10.1364/OL.41.004959 Barnes BM, et al: "Three-dimensional deep sub-wavelength defect detection using l=193