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imaging data. Our offices are located at the Clinical Research Center (CRC) in Malmö, next door to the Department of Obstetrics and Gynecology at Skåne University Hospital. This project aims to investigate
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using Cell Painting and high-content imaging. Deep learning and multivariate methods, both supervised and unsupervised. Development of software and pipelines for analysis of large-scale image data
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Description Job description Driven by the urgent challenges of climate change and energy security, energy systems are undergoing a paradigm shift toward a fully renewable and power-electronic-dominated future
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models using advanced operator learning and physics-informed AI techniques, leveraging high-resolution X-ray imaging data and high-performance computing (HPC) resources. The position offers a unique
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, BCI), physiological data, and medical image/microscopy analysis. Excellence in foundational and applied research, demonstrated by publications in leading AI/ML and medical imaging venues (e.g., MICCAI
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dynamics to cellular metabolism. The student will receive broad training in cell culture, genome engineering, live-cell imaging, biochemical assays, proteomics, and computational data analysis, and will work
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Cancer is a leading cause of death globally, and analyzing digital pathology images for cancer diagnosis and treatment is a complex problem due to the high data volume, variability, and computational
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and survival in host cells. Through a combination of microbiology, imaging, molecular biology, and translational modelling, the PhD student will generate data to support the design of biofilm-resistant
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Proteomics unit you will be responsible for data management and infrastructure, implementation and development of analysis pipelines. You will work on different datasets and help our users with image and
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world-leading research environment through the development of paradigm-shifting knowledge about bio-based wood adhesives in three research areas: raw materials and formulations, aspects of adhesives, as