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- Universidade do Minho
- International Iberian Nanotechnology Laboratory (INL)
- University of Newcastle
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Exchange function and created Newcastle Innovations —bringing together expertise in commercialisation, partnerships and engagement into a more integrated, ambitious and outward-facing model. We are building
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function and created Newcastle Innovations —bringing together expertise in commercialisation, partnerships and engagement into a more integrated, ambitious and outward-facing model. We are building a dynamic
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Engineering, Mechanical Engineering, or related fields; b) Experience in the numerical modelling of acoustic phenomena; c) Experience in using acoustic tools, namely ultrasound-related, for liquid and solid
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prioritise RD as a mechanism for ecosystem resilience. The project will use Agent-Based Policy Modelling (ABPM) to simulate how actors such as land managers, farmers, local authorities, and conservation
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effects, so studying different models of quantum computation enables us to pinpoint different ways to get quantum systems to work their magic. The postdoctoral Researcher is expected to work jointly with
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-economic study, design and analysis of integrated systems. Experience with energy system modeling/simulation tools (e.g., MATLAB/Simulink, Modelica, and COMSOL Multiphysics), energy systems analysis
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, specialized training). Preferential factors: Previous experience in risk and resilience assessment and management of civil infrastructure. Previous experience in structural modelling and data analysis applied
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Python/Matlab or similar. Other Valued Skills Experience in FDTD simulations of advantage. Experience in quantum photonic principles for quantum sensing such as ODMR. Quantum Chemistry/Modelling
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dynamic thermal simulation of buildings with standard lightweight façades. Development of an innovative numerical model in EnergyPlus that allows for the simulation of buildings with dynamic thermal
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. Characterise experimentally WAAM-produced samples to provide data for model calibration and validation. Optimise process parameters using numerical simulations and Machine Learning-based predictive models