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Life and Health Sciences Research Institute (ICVS), from the School of Medicine (EM) of the University of Minho | Portugal | 8 days ago
submit in the application process a Declaration of Honor regarding the benefited Research Fellowships, issued as defined in the model attached to the present public notice, in order to assess whether
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microscopy, spectroscopic ellipsometry, SEM and others. - Closely coordinate with teams performing materials characterization, bond strength testing and modeling. The successful candidate will work in a highly
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wind propulsion devices. The work will focus on data-driven modelling, routing optimization, and control strategies for wind-assisted vessels. Relevant research topics include voyage optimization under
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with numerical modeling, energy system optimization and possibly machine learning to guide energy transitions towards net-zero systems. The research supervisors have prepared multiple potential projects
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and accelerate the development of more high-performing PNSEs. The ultimate goal of the project is to develop, implement, and validate novel deep-learning models for molecular dynamics and coarse-grained
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this role, you will contribute to TOZCA’s whole‑aircraft noise prediction capability, ensuring acoustics are robustly represented within the project’s wider modelling framework. You will develop, apply and
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this role, you will contribute to TOZCA’s whole‑aircraft noise prediction capability, ensuring acoustics are robustly represented within the project’s wider modelling framework. You will develop, apply and
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needs. Conduct comparative and functional analyses to model biological processes, gene networks, and metabolic pathways. Contribute to the preparation of grant proposals and supporting materials. What is
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Life and Health Sciences Research Institute (ICVS), from the School of Medicine (EM) of the University of Minho | Portugal | 9 days ago
the benefited Research Fellowships, issued as defined in the model attached to the present public notice, in order to assess whether the candidates meet the necessary conditions to be able to benefit from
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statistical methods including multilevel modelling, psychometric scale validation (EFA/CFA), structural equation modelling and causal inference approaches appropriate for complex education datasets. Advise