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in sensitive contexts, such as cybersecurity. Then, based on the knowledge acquired, they should conduct state-of-the-art research on defence mechanisms, methodologies, and tools, assessing
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: Recommender system for biological control agents against plant pathogens”, “2023.14580.PEX”, ”DOI: https://doi.org/10.54499/2023.14580.PEX ”, funded by the Fundação para a Ciência e a Tecnologia, I.P. through
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 5 days ago
integrated into the educational project of a higher education institution, within the project “PyroSENSE Continuous monitoring of cardiovascular complications using high-tech solutions based on pyroelectric
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, tissue and organ abnormalities, and disease progression. Creation of novel disease models. Objectives: To establish in vitro microphysiological disease models based on human cells and tissues derived from
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. 5) Testing: Rigorous validation of simulation models and the effectiveness of suggested strategies through multiple race scenarios. Optimisation of algorithms based on the results obtained and
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Area: Chemistry Project Title: Molecular Bioengineering in Health ERA Chair Summary and Workplan Peptide synthesis for the controlled release of antimicrobial agents Bacterial resistance to common
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legislation. Procedure Reference: IT137-25-329 I - Legal admission requirements I.I - Grant Recipients: Masters in Mechanical Engineering, enrolled in the PhD Program in Mechanical Engineering. Knowledge in
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Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa. | Portugal | 8 days ago
» Biochemistry Technology » Biotechnology Medical sciences » Health sciences Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Portugal Application Deadline 12 Sep 2025 - 23:59 (Europe
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product development, especially in the field of mobility (20%); - Demonstration of 3D modeling knowledge (20%); If the jury considers that do not have the conditions for deciding based on Curricular
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artificial intelligence-based algorithms to optimise operation and predict anomalies in water distribution networks. The algorithms developed should identify patterns and anomalies that indicate the presence