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algorithms for asthma. The methods to be employed will include cell culture, transcriptomics, proteomics, multiplex assays, flow cytometry, and machine learning. This project combines expertise in cell biology
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dynamic mobility of UAVs, limited onboard energy, and the stochastic nature of 3D wireless channels. Therefore, this project aims to develop novel reliable resource orchestration solutions for AEC by
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and visualization in a Microbial Cell Atlas. This position aims to develop key software components to enable this mission. The results of this project will be used to track new pathogens, combat
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Information Additional comments Education: Master's degree (M.Sc., 2nd year) or equivalent engineering school diploma in Cell Biology, Oncology, Biophysics, or Physical Chemistry of (Bio)interfaces. • Technical
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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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persistence in chronic infections (Salmonella, Pseudomonas, and Achromobacter) by integrating spatial modelling, single-cell transcriptomics, advanced imaging data, and machine learning approaches. The goal is
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to develop 2D and 3D NMJ models for DM1, consisting of different combinations of patient-induced pluripotent stem cell (hiPSC)-derived neuronal and muscle cells, allowing the dissection of pathological
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perturbation-based GRN inference for single-cell and spatial multi-omics data, to boost GRN quality and add the cell type and tissue heterogeneity dimensions to causal regulatory analysis. A deep learning
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well as train and support lab scientists on various cell biology and microscopy techniques including live imaging using confocal microscopy Train and support lab members on standard and emerging molecular biology
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. Experience in mammalian cell culture and molecular biology techniques are preferred. Training will be provided on the methods required for successful project completion. Teamwork, motivation to learn new