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, land cover, population) Classification of burned area and active fires using medium resolution data from the Landsat and Sentinel programs Spatiotemporal analyses of fire behaviour in different contexts
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sustainable future together, we wish to make a difference. Do you want to be involved and contribute to our development? Together, we can create a sustainable future through knowledge and innovation. We believe
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to make a difference. Do you want to be involved and contribute to our development? Together, we can create a sustainable future through knowledge and innovation. We believe that knowledge and new
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disease, in particular cancer. You address this question using both different in vitro models, with the focus on embryonic stem cells and intestinal (cancer) organoids, and with tissue biopsies from
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ability to comfortable processing these data using tools like Seurat, Scanpy, or QuPath. Proficiency in Python or R, coupled with familiarity with machinelearning frameworks (e.g., scikit‑learn, PyTorch
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crystallographic data. The project focuses on implementing different data processing and analysis methods relevant to time-resolved crystallography. This will involve working with automatic data processing pipelines
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management skills using statistical software (e.g., SAS, R or Python) Experience in writing and publishing scientific articles in epidemiology, psychiatry, or related topics Good communication skills in
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++, ROS, Matlab, Python etc.). You should have a strong vision to participate in developing research findings proposals. You will need to represent the group, both in Sweden and abroad and hence have
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pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings. Coordinate the collaboration between the chronobiology lab (led by Dr. Paul Petrus) and the
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in mouse models and cell cultures. Analyze and interpret omics data using bioinformatic pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings