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- MOHAMMED VI POLYTECHNIC UNIVERSITY
- NTNU - Norwegian University of Science and Technology
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Field
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Forecasting system developed by CSIRO. Along with a $42,000 p.a. scholarship for three and a half years, the student will have the opportunity to undertake a funded 60-day industry placement with one of our
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and pollution prevention, with opportunities to engage in applied environmental solutions, brownfield redevelopment, and community-oriented research. AI-Enabled Detection and Forecasting of Invasive
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forecasting. Excellent organizational and project management skills. Excellent communication skills, both oral and written. Comfortable working independently and in team settings. APPLICATIONS Please submit a
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, droughts, heatwaves, …). Knowledge of uncertainty quantification and probabilistic forecasting. Familiarity with sectors such as water resources systems, disaster risk mapping, agriculture, water-dependent
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highly skilled Postdoctoral Fellow with a proven dual‑mode research profile capable of independently performing laboratory experiments and coding predictive AI models in Python to forecast biomaterial
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laboratory experience in areas relevant to the project, namely: needs diagnosis and assessment; development of artificial intelligence-based forecasting models; and development of optimal control models
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forecasting. Build data fusion pipelines (e.g., combining model outputs with imagery, weather, soil, and management data) to deliver prescriptive BMPs for nutrient and water management, planting decisions, and
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landslide and rockfall forecasting: the lack of physically grounded, early precursors of failure. The core hypothesis is that macroscopic slope collapse is preceded by changes in local deformation, expressed
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systems, knowledge management, and decision-support tools Forecasting, monitoring, and early warning systems Environmental sustainability and sustainable development Through strong collaboration with
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. The core research objective of this PhD is to design and evaluate “latency hiding” methods for immersive networked interactions. This involves (i) developing predictive machine learning models that forecast