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morphology imaging, and spatial transcriptomics—to identify altered cell states and mis-patterning events. The aim is to integrate computational and experimental approaches, including validation in vivo
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(University of Bern, GTK). Take part in data curation, pre- & post-processing of datasets. Undertake in a limited number of laboratory experiments in co-operation with other team members. Take part in
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approach that includes advanced bioimaging and image analysis, cell biology and genetics, and omics technologies. Qualifications We invite applications from candidates with a background in cell and
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models in collaboration with our international collaborators. You would also develop advanced image analysis schemes to analyse the experimental data. Your focus would be to investigate the effect
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natural language processing techniques to analyze digital content such as images, videos, and textual content that relate to human-nature relationships, with a focus on data derived from digital platforms
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Chinmey Dwibedi’s group at MIMS, Umeå, through the NORPOD program. Summary of the project The post-doctoral project aims to uncover genetic and adaptive mechanisms of the tumour associated microbiome in
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for separately: www.helsinki.fi/en/research/doctoral-education/the-application-process-in-a-nutshell . The requirements for pursuing a doctoral degree at the University of Helsinki can be found at https
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researchers (for further information, please see: https://blogs.helsinki.fi/viikki-postdoc/ ). Application and selection procedure To apply, please send the following documents in a single pdf file: * A letter
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processes contributing to cancer. The candidate We seek a motivated candidate with a strong interest in computational cancer research, who is enthusiastic about applying deep learning methods to cancer data
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regulatory processes contributing to cancer. The candidate We seek a highly motivated candidate with a track record of statistical models, network science, and/or computational tool development dedicated