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on the development, theoretical analysis, and optimal implementation of numerical methods for systems governed by multiphysics and multiscale differential models, including the use of parallel computing architectures
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for a postdoctoral research fellow position in the Mental Health for All Lab (MHFAL) at the Department of Global Health and Social Medicine at Harvard Medical School in Boston, Massachusetts. The work
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI SCIENZE E TECNOLOGIE AGRO-ALIMENTARI | Italy | 10 days ago
Description The work plan will be structured into the following phases: • analysis of the state of the art on the sustainable management of water resources in irrigation districts, with particular reference
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About the Role We are seeking a creative and enthusiastic Bioinformatician to lead on the design, conduct, supervision and publication of bioinformatic analyses in the Modernising Medical
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and purification capabilities. By developing reliable, general‑use methods for small‑molecule analysis, enzyme characterization, and chromatography workflows, this position directly supports a wide
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with experience in zebrafish work, advanced microscopy (in vivo imaging, confocal microscopy), host–pathogen interactions, innate immunity, vaccination, gene expression analysis, or cell-based assays
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cognitive-neuroscience methods, particularly structural or functional MRI, EEG or MEG. Experience with neuroimaging analysis, functional or structural connectivity, computational morphometry or signal
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, and system configuration, supporting accurate financial reporting and operational decision-making. The role performs reconciliation and financial analysis activities and serves as a key liaison with
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Engineering, or a related field. Familiarity with Excel, MATLAB, Python for engineering calculations and data analysis. Analytical and problem-solving skills, with the ability to work independently and document
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join our accomplished team! Your working area: The research group Statistical Analysis and Inference (STAIN) (https://stain.univie.ac.at/ ) at the Department of Statistics and Operations Research (https