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environment focused on physics‑informed AI tools for materials design and characterization. In a collaborative project with industrial partners, you will work on developing physics‑informed models for heat
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geoinformatics and spatial data science, including demonstrated knowledge of GIS, spatial analysis, spatial modelling, and GeoAI. Experience and expertise in WebGIS development, familiar with the core technologies
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The overall aim of this PhD project is to understand the influence of climate-driven changes in vegetation cover and winter conditions on habitats and food webs of Arctic/alpine lakes. Climate change is
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the influence of climate-driven changes in vegetation cover and winter conditions on habitats and food webs of Arctic/alpine lakes. Climate change is promoting the expansion of terrestrial vegetation, which
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learning approaches and related data-driven methods to discover new decoding strategies or even new code structures; jointly optimizing quantum codes and their decoders for realistic noise models and
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. Subject description Robotics and artificial intelligence aim to develop novel robotic systems that are characterized by advanced autonomy for improving the ability of robots to interact with the surrounding
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
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approach and enjoy combining methods and perspectives from different fields, such as physics, acoustics, computational modelling, and biology. You are driven by a desire to understand complex phenomena and
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
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research in data-driven nutrition, health, and food science. With large-scale diet and health data, omics data, biomarkers, digital food and health services, we establish predictive models for evaluation