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multimodal data analysis. Experience on image processing via machine learning. Programming skills (e.g., Python) are required. Ability to communicate effectively in both spoken and written English. Merits
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, and manipulation of high-dimensional imaging and mass spectrometry data Experience in designing and maintaining reproducible and scalable analysis workflows Solid foundation in statistics and machine
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look forward to receiving your application! At the intersection between AI and single atoms. Your work assignments We are looking for a PhD student with a background in machine and deep learning with
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The postdoctoral researcher will work with computer-based analytical methods and large databases to develop theory and methodology for utilising aggregated data from archaeology, genetics, and linguistics, thereby
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mathematics, data science and machine learning for image recognition. Moreover, you will develop methods and software that will allow new characterization of nanoscale materials. Therefore, your research will
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data types (transcriptomics, proteomics, imaging). AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional relationships from perturbation data. FAIR
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, deep learning, and human computer interaction. Furthermore, this university is Sweden’s leading university in industrial collaboration. The Machine Learning (ML) subject at the department
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to tumour tissue images have improved characterisation of cancer tumours in clinical routine. However, traditional machine learning models require annotated data and are limited in scope, while foundation
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experiments, and machine learning (ML) to understand and predict multiscale transport phenomena in fuel cell systems. In particular, the postdoc will bridge pore-scale simulations and macroscale performance
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for multimodal machine learning, combining large-scale image data with molecular profiling and clinical data. This includes, for instance, research on deep learning-based image analysis and data assimilation