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to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven
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, confocal imaging, live animal IVIS and CT-PET machines, X-ray radiation, XCELLigence, Seahorse, ultracentrifuge, Proteomics (Mass spectra), HPLC, etc Conducts background research, independently design
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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for imaging Apply for this job See advertisement About the position Position as PhD Research Fellow in machine learning available at Department for Informatics with the research group Digital Signal Processing
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Requirements: PhD in geophysics, geology, geomatics, geodesy, geomatics, electrical engineering, computer science, natural hazards, or a related field Demonstrated skills in remote sensing, image processing
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Development of a simple functional prototype with a data ingestion and pre-processing pipeline. Preliminary evaluation with exploratory models to validate the concept and define the final architecture. 4
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Development Fund (ERDF) though the “Programa de Inovação e Transição Digital” (COMPETE2030), taking place at the Laboratory of Image and Video Technology of Faculty of Sciences of the University of Beira
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seeking enthusiastic, full-time post-doctoral Flatiron Research Fellows to work on information processing in biological networks and nonequilibrium thermodynamics of living systems. Current areas
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fields. Strong background in medical image analysis and signal processing. Proficiency in programming, particularly in Python. Demonstrated ability to publish in peer-reviewed journals. Motivated, self