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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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). Applying advanced statistical and machine learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development
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machine learning Data analysis and advanced statistics Economic and social transformations related to digitization Experince when it comes to programming (preferably Phyton) and in the use of modern tools
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will be made for all categories of stakeholders to support the process of job matching. Where to apply Website https://resurseumane.ase.ro/pnrr-cf_178-jobkg-a-knowledge-graph-of-the-romanian
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statistical machine learning techniques to mine self-reports and sensor data to gain new insights towards assessment and longitudinal monitoring of bipolar disorder; b) work on sleep datasets exploring
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interdisciplinary and experiential learning to join the Source Project , Binghamton University's distinctive first-year research program in the Humanities and Social Sciences. The position begins August, 2026. PhD in
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taken relevant course work in chemistry, biology, or engineering. Demonstrated ability to learn new and innovative procedures quickly Demonstrated knowledge of basic computer software (Microsoft Word
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or Python to analyze data and experience with statistical, machine learning, and data science approaches. Prior experience working in teams on collaborative projects. Knowledge, Skills and Abilities
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Bachelor's degree and relevant work experience. Experience Excellent organizational skills and attention to detail. Must have experience or be extremely motivated and eager to learn neuroimaging processing
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Eligibility criteria Instrumental optics and imaging (microscopy, camera detection) for biology. Skills in coding and experiment control. Basics of machine learning and/or signal processing. Teamwork