11 non-coding-"Data-driven-Materials-Modeling" Postdoctoral positions at Leiden University
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) Application Deadline 14 Sep 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not
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) Application Deadline 14 Sep 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not
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Aug 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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) Application Deadline 31 Jul 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not
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behaviour Researcher Profile Recognised Researcher (R2) Application Deadline 25 Jul 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job
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integrates seamlessly with other data and compute infrastructure (such as HuggingFace, DataVerse); Contribute to the OpenML codebase and platform by making code more maintainable and reviewing community
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satellite-based estimates of trace gas emissions and albedo during and after wildfire events we will evaluate and improve the modeling of fire-related non-CO2 emissions and albedo changes. This will lead to
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industry come together. Working at our faculty means being part of a dynamic, international environment where both staff and students are driven by curiosity—not only to expand fundamental knowledge
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Psychology. The faculty is home to approximately 7,000 students and 1,000 staff members. Our institutes are dedicated not only to education but also to groundbreaking research that pushes the boundaries of our
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designed for spatio-temporal data do not allow assessing the impact of interventions without capturing causal links. In this project, we aim to design algorithmic solutions grounded in causality