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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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decision systems for pricing and market strategies. In particular, algorithmic repricing tools allow real-time price adjustments based on predefined rules or machine-learning techniques. While recent
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, statistics and scientific computing. * Proficiency in a scientific programming language, particularly Python, and the ability to develop reproducible processing procedures. * Knowledge of machine learning and
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This multidisciplinary thesis requires strong expertise in several of the following areas: Robotics, computer vision, control systems, dynamic modeling, signal processing, or machine learning
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, GC-MS/MS, and advanced NMR approaches. - **Activity 4:** Multivariate statistics and machine learning to identify microbial and chemical biomarkers of resilience and reveal the interactions linking
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of Research Experience1 - 4 Additional Information Eligibility criteria We are looking for a doctor in particle physics with less than two years of experience after the PhD. Experience in machine learning and
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data) will help validate observations and refine predictive models. Automated monitoring tools (scripts, dashboards, alerts) incorporating machine learning algorithms or statistical methods will be
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archaeological and historical contexts is also required. Additionally, the ability to perform *ad hoc* data processing (multivariate statistics, machine learning, etc.) is desirable. Proficiency in programming
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of technological disruption driven by Artificial Intelligence, we propose to analyze the data and quantify these similarities by exploring various applications of machine learning methods. With the advancement of AI
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, ideally molecular dynamics and/or DFT. Scientific programming skills, particularly in Python, are expected. Familiarity with machine learning or generative AI methods applied to materials would be a strong