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and documented background in machine learning, deep learning, data analysis and programming. Previous experience in research and knowledge in bioinformatics, biophysics, biochemistry, molecular biology
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to intravital microscopy), electrophysiology, respirometry, microfluidics, organoid cultures, bioprinting, and excellent opportunities to work with various in vivo models. Infrastructure and expertise in various
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, which is crucial for rutting, using machine learning. Second, we will develop new systems to integrate data from radar and lidar sensors mounted on drones and forestry machines to improve future real-time
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in vivo models. Infrastructure and expertise in various so-called omics technologies, single-cell biology, bioinformatics, drug development, and more are available locally through the SciLifeLab
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Injection Systems (CIS) — natural protein machines used by bacteria to deliver molecular cargo. The group's mission is to understand the structure, function, and application of CIS for use in both
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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software development. Documented experience or interest in Artificial Intelligence and Machine Learning development, Proficiency in written and oral communication in English. Place of employment: Karlskrona
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of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. More information about the total announced post-doctoral positions within in
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learning models—alters the way software systems evolve (SE4AI). A strong focus will be on the post-deployment lifecycle of ML components, including drift detection, model decay, retraining triggers, and
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, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software