31 data-"https:"-"https:"-"https:"-"https:"-"Grenoble-INP---LCIS" positions at Utrecht University in Netherlands
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PhD Position in AI and Data Science for Modelling and Analyzing Reading Text Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40
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Bachelor’s and Master’s levels (approximately 10-15% of your time). Where to apply Website https://www.academictransfer.com/en/jobs/357222/phd-position-in-ai-and-data-sci… Requirements Specific Requirements
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18 Nov 2025 Job Information Organisation/Company Utrecht University Research Field Biological sciences » Biodiversity Environmental science » Ecology Environmental science » Global change Researcher
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deadline: 18 January 2026 Apply now Within the RegioDeal Foodvalley (RDFV-II) programme, you will contribute to advanced analyses of air quality monitoring data, emission modelling and scenario studies
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conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more information, please visit Working at Utrecht
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is mainly because, until now, we have lacked the tools and data to quantify emissions from deforestation and degradation in the tropics with sufficient accuracy and temporal consistency, and to capture
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hybrid (symbolic and sub-symbolic) AI approaches to help users formulate and translate natural language questions into structured representations that can be linked to geospatial data sources and workflows
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PhD Position on Requirements Engineering and Spec-Driven Development Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application
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You are dedicated scientist with a background in chromatin biology and/or gene regulation and experience in cell engineering, molecular cloning, genomics, and computational data analysis workflows. In
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering