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experiments. • Practical knowledge of process engineering, Power BI and Lean manufacturing. • Knowledge of fault prediction and machine maintenance in industrial settings (TPM) is desirable. • Fluency
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independent research aligned with the aims of the Addiction & Decision Neuroscience Lab (ADN). Current work focuses on cognitive modeling of decision-making in both laboratory tasks and real-world settings, as
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integrates clinical, molecular, and real-world data with emerging computational approaches, including large language models, predictive modelling, and multi-omics data integration. The lab coordinates and
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approximately 10–15% of women of reproductive age. The project aims to integrate fragmented biomedical evidence into structured resources and predictive models that support non-animal approaches to chemical
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Number BAP-2026-482 Is the Job related to staff position within a Research Infrastructure? No Offer Description In the last decade, ML models taking inspiration from the brain and biological neurons have
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of Finland–funded TRANSITION-MODEL project at Aalto University’s School of Engineering, Department of Energy and Mechanical Engineering. The project advances predictive maintenance from offline modelling
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Systems platform; Oversee the aggregation and indexing of complex institutional datasets into unified information pipelines, enabling real-time predictive analytics and executive visibility dashboards
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. Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data. Generate and test hypotheses and
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experience required in an analytical or information specialist role within an academic, nonprofit, corporate or consulting setting. Deep understanding of statistical and predictive modeling concepts, machine
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(PAPROG) with the overarching goal to develop an operational modeling tool for glacier hazard prediction and analysis. This PhD will benefit from technical support funded by the project and collaborations