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, and machine learning methods. Using regression analysis and vector autoregression (VAR) models, the study examines the relationship between macroeconomic variables and the performance of various
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, numpy, scanpy, Squidpy, matplotlib, and others for single-cell and spatial analysis Interest in kidney research Exposure to machine learning and deep learning concepts Demonstrated ability to participate
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leadership in the design, execution, and analysis of real-world evidence (RWE) studies. Oversee the development and validation of the common data model and the data integration platform for use in healthcare
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3 Mar 2026 Job Information Organisation/Company UNIVERSITE LE HAVRE NORMANDIE Research Field Computer science » Computer systems Computer science » Database management Computer science » Modelling
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understanding of all models of monitors and ECG machines utilized, be able to perform configuration on any specific monitor, replace defective equipment, report any equipment malfunctions to initiate repair, and
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insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Research Grant or Time-limited
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development of specialised APIs and lifecycle management of the machine learning model. This role will require a strong understanding of electrical engineering and power systems principles in order to encourage
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to study chromatin and gene regulation in mammalian cells and human disease systems. Current ongoing projects include: statistical modeling and advanced machine learning/AI method development for predicting
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materials using statistical mechanics, molecular simulations, and machine learning. Expectations Candidates will be responsible for: Developing multi-scale modeling methods for polymeric materials, using
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Models to push the frontier where computer vision, physics simulation, and embodied AI converge. Join Us! This position is part of a collaborative research programme between the University of Amsterdam