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for visualization of scientific data. Currently, InfraVis employs over 50 experts across nine universities. CIPA is Lund University’s local infrastructure for image processing and analysis. CIPA is also the
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. Research will have a strong focus on computational analysis or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or
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and training in data analysis, scientific communication, and collaborative research. About the position We are seeking a PhD student who will advance the understanding of chemical contaminants in food
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within linear algebra, calculus, numerical linear algebra, optimization, statistical machine learning, computer vision, 3D image processing, visualization, material science, deep learning, and software
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data integration, analysis, visualization, and data interpretation for patient stratification, discovery of biomarkers for disease risks, diagnosis, drug response and monitoring of health. The precision
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. The candidate will apply and further develop computational workflows (e.g., R) for compound identification in complex matrices, with emphasis on R‑based data evaluation and visualization. The position also
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sample preparation for structural proteomics, i.e. wet lab work and mass spectrometry, followed by data analysis and visualization of data for users of the infrastructure. We envision that you will start
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and spatial omics analyses performing quality control, preprocessing, integration, annotation, visualization, and downstream statistical analyses contributing to data management, workflow development
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Value Chains, funded by The Bridge initiative. This project focuses on AI-driven data integration, forecasting, scenario simulation, and visual decision-support systems for sustainable forest-based supply
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should have documented background in the following areas: Electrodynamics Data analysis for scientific applications Programming (e.g., Matlab, Python, C, C++) for scientific applications Previous