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translational focus in pathology, clinical chemistry and medical and clinical genetics. The department belongs to the Faculty of Medicine at Umeå University and has approximately 90 employees who conduct research
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algorithm-based technologies in service occupations, with a focus on how collective bargaining and other forms of collective worker voice influence these strategies and worker outcomes. The US research will
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data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms Assist with organizing large scale multimodal neuroimaging datasets, brain
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Qualifications - Experience in developing algorithms for analysis of biological data. - Experience with single cell and spatial transcriptome data analysis. - Experience in supervised and unsupervised machine
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that integrate simulation, machine learning, and data analysis. Numerical optimization methods (e.g. machine learning including deep neural networks, reinforcement learning, data mining, genetic algorithms
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, numerical optimization, numerical partial differential equations, and parallel computing. The Researcher will join a project developing parallel high-order meshing algorithms from medical images and parallel
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Systems will participate in the research efforts of developing systems integration, analysis, design, control, and/or optimization models and algorithms for smart energy systems to enable smart and healthy
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Location Indianapolis Position Summary Are you passionate about genomics, big data, drug discovery, and AI/machine learning? Interested in advancing cutting-edge multi-omics research to explore genetic and
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algorithms and codes for AI-enabled digital twin technologies. Design advanced numerical algorithms for partial differential equations and optimization problems related to digital twin technology. Implement
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learning methods to improve the understanding, treatment and prevention of human disease. The successful candidate will develop novel statistical and machine learning algorithms to address key challenges in