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model and biological membranes. The experimental data will be paired with results from molecular dynamics simulations to provide a complete characterization of the biophysical properties of the imaged
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KTH Royal Institute of Technology, Scool of Electrical Engineering and Computer Science Job description Cellular morphology reflects fundamental biological processes such as division
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computational imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely
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imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely connected
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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at the Department of Cell and Molecular Biology. The Elf group works across traditional disciplinary boundaries to explore life at the molecular level. We build physical models of key biological processes and develop
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related field and have previous academic experience in machine learning. The candidate should have a strong background in metrology and medical image processing. Active participation and collaboration
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, tissue sections, RNA/DNA, tabular data) for predictive modelling using software such as Python Documented experience of neural networks, image processing, deep learning algorithms, and data visualization
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of formulating them, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment
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scenarios. The research combines field experiments, AI-based analysis of museum specimens, and advanced climate modeling to provide process-based insights into the ecological and economic consequences