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assess the integration of participatory monitoring approaches, remote sensing and local natural resource knowledge to improve decision making in the implementation of nature based solutions and inform
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observations. Your major challenge is in model development, and there is room for you to develop machine learning applications in the field of firn modelling. If successful, your work will lay the foundation
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August 2025 Apply now Atmospheric science and climate change assessments often focus on winter and summer. In this fully funded PhD position you will instead study the weather of spring and autumn. Your
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similar field; expertise in programming skills and statistical data analyses, including machine learning; affinity with environmental exposure modelling and high-performance computing; strong reporting and
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interest in environmental health and Exposome research; expertise in programming and quantitative data analysis, including machine learning in R/Python; affinity with bioinformatics; strong collaboration
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Apply now Are you passionate about the future of education and AI? Join us as a PhD candidate to explore how adaptive AI can enhance innovative teaching and learning. This interdisciplinary project
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Universities (CAO NU)); 8% holiday pay and 8.3% year-end bonus; a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU. In addition to the employment conditions laid
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for delta adaptation and development under uncertain changing conditions? How can we sequence measures that are made in different regions, e.g. using modelling tools? What is the timing of decisions and what
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experiments in controlled conditions aiming at simulating natural environments; 3) You will participate in arctic campaigns and use the methods developed to shed light on methane cycling in permafrost regions
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significant controversies regarding the exact mechanism of action. To understand the molecular and biophysical principles of protein folding, we aim to build fully controllable chaperone-like machines using DNA