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will build an experimental and computational platform based on 3D-printed, brain-mimetic tissue models with tunable transport properties, where interface transport can be measured and predicted
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the following research areas providing a template for relevant directions: - Embodied Intelligence for Soft Robotic Systems - Foundational Models for Adaptive Soft Robots - Real-Time Adaptive and Stiffness-Aware
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areas providing a template for relevant directions: - Embodied Intelligence for Soft Robotic Systems - Foundational Models for Adaptive Soft Robots - Real-Time Adaptive and Stiffness-Aware Control
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predictive models for evaluation of the role of dietary in health and disease and establish personalized dietary strategies for more effective disease prevention. In many cases, the work involves time series
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, better adapted individuals can be selected at the seedling stage using only genetic data, accelerating the breeding cycle. Incorporating information about plasticity can aid genomic prediction modeling
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strategic raw material (CRM) deposits within Paleoproterozoic cover sequences that overlie an Archaean basement. Existing structural models for the cover rocks predict that crustal-scale fault and shear zone
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Paleoproterozoic cover sequences that overlie an Archaean basement. Existing structural models for the cover rocks predict that crustal-scale fault and shear zone systems extend into the basement and that structural
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University Duties This PhD project is part of the AFLOW consortium supported by the Swedish Energy Agency and focuses on multi-scale modelling of aqueous organic redox flow batteries, to build a predictive
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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
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from vascular lesions and blood, combined with genetic, clinical/epidemiological and imaging parameters from patients. We also perform in depth functional studies in animal and cell culture models