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HCI and cybersecurity, to cancer research tools and methods for numerical analysis and machine learning. The research work takes place in a multidisciplinary team with a focus on image processing with
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spectrometry. The project involves developing characterization methods using mass spectrometry (FT-ICR, TOF-SIMS) and imaging techniques (SEM, TEM) for both biological and inorganic materials. Responsibilities
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analytical chemistry and mass spectrometry. The project involves developing characterization methods using mass spectrometry (FT-ICR, TOF-SIMS) and imaging techniques (SEM, TEM) for both biological and
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https://www.lunduniversity.lu.se Street Paradisgatan 5 Postal Code 221 00 E-Mail karin.falth@hr.lu.se Phone 0703258022 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E
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available1Company/InstituteKTH Royal Institute of TechnologyCountrySwedenCityStockholmPostal Code11428StreetBrinellvägen 8 Contact City Stockholm Website http://www.kth.se Postal Code 11428 STATUS: EXPIRED X
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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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fluorescence microscopy, image analysis, and sample preparation for sequencing and multi-omics analyses. The main model organism will be Bacillus subtilis, but other bacteria as well as fungal species including
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into operational decision‑support tools for farmers, in close collaboration with an industry partner. The project focuses on automated rumen‑fill assessment using 3D imaging, computer vision, and predictive
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ecology & physiology, generative models, artificial intelligence-based image super-resolution, and three-dimensional reconstruction. The scholarship is full-time for two years with a start date of February
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imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring