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two main directions: i) process-based studies and modelling - from local scale water balance studies to continental water resource assessments, and ii) statistically based regional and large-scale
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, surveys, faculty research, and business intelligence programs. Provides strategic direction for dashboards and predictive modeling, empowering leadership with real-time insights and key performance metrics
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FCT code 2023.17217.ICDT and DOI https://doi.org/10.54499/2023.17217.ICDT . , funded by COMPETE 2030 by Portugal 2030, and by the European Union, financial support from national funds/OE through
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controllability • Learning and calibration strategies for uncertainty-aware language model prediction • Knowledge-augmented and neuro-symbolic approaches for language-based reasoning • Evaluation and design of LLM
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. Ingunn Wehus (i.k.wehus@astro.uio.no ). The ERC-funded Origins project has the goal of modeling the diffuse sky from 1 micron to 1 GHz, including contributions from the Cosmic Infrared Background (CIB
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of the critical barriers to onshore renewable energy acceptance. Our physics-informed machine learning model will provide the first reliable AM prediction capability, addressing a significant industry need. This
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assessments. Builds predictive models and forward-looking analyses including what if scenarios to understand impact of external factors and internal decisions  Leads the law school-wide accounting, budgeting
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sensor data with gas transport models for improved detection. · Developing numerical methods to enhance prediction accuracy. · Collaborating with MIRICO’s Digital Team to optimise performance
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machine-learning approaches for the analysis and integration of complex neural and movement data, supporting new insights into the mechanisms underlying human motor control and rehabilitation. About the
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vehicles such as lipid nanoparticles (LNPs) • Create experimental protocols for cancerous, healthy human and microbial model cell membranes. • Establish predictive models for peptide-induced transport