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Field
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representation methods for accelerated inverse design Large language, diffusion & graph neural models for materials discovery Fine tuning and architecture optimisation of foundation models Inverse design of next
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creates the necessary conditions for a rewarding career. The School of Biomedical Engineering (SBME) at the University of British Columbia (UBC), Vancouver campus, invites applications for a full-time
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to analyze wave interaction with natural coastal ecosystems under varying conditions. • Optimize the model to predict shear coefficients, drag forces, and energy dissipation. 2. Experimental Calibration and
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RESEARCH FELLOW IN ARI(TRANSITION RISKS IN IMPLEMENTING FOREST CARBON INITIATIVES IN SOUTHEAST ASIA)
accumulations of carbon in the atmosphere (achieving “net zero” emissions) by 2050 and involve major structural and behavioural changes globally. Forests capture carbon from the atmosphere, a proportion of which
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performance under diverse operating scenarios, including power limitations, ambient environmental conditions, and human-device interactions • Validate simulation models using experimental data or benchmark
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for this position must be able to analyse data from fisheries and/or aquaculture and prove experience from designing, collecting, modelling and publishing such data. Research experience in Norwegian or Nordic
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neurodevelopmental and neurodegenerative conditions, such as Down syndrome (Lattke et al. Nature, under revision, Bass et al, iScience, under revision; Peter, Real et al, Reviews common under revision; Real et al
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imbalances in the gut microbiota contribute to chronic inflammatory conditions, colorectal cancer (CRC), and immune dysfunction, with an emphasis on discovering biomarkers and developing microbiome-based
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apply advanced computational tools and reproducible workflows to interrogate large-scale, liquid chromatography–mass spectrometry (LC–MS)-based comparative metabolomics datasets spanning a range of model
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees