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and enthusiastic researchers to exploit the unique and transversal capabilities of analytical research infrastructures in tackling the challenges associated with sustainable development and industrial
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on the development and characterization of different ionic liquids (ILs) or eutectic systems (ESs) (position 1) and metallic nanoparticles (MNPs) (position 2), which will be used respectively in the two positions
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Advisor: Ana Paula Martins Falcão Flor (ist13814) Co-advisor(s): Jónatas Valença (ist417176), LNEC. Organic Unit: Scientific Area of Construction Scholarship Theme: The work aims the development
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development. It is one of the world's leading research institutions in its field and offers natural and social scientists from around the world an inspiring environment for excellent interdisciplinary research
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(SustainCARE, https://doi.org/10.3030/101220359 ), led by Dr. Yun Liu. SustainCARE brings together heritage science, building physics, advanced modelling, and climate-conscious preservation, offering a unique
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focuses on the development of secure and trustworthy AI for resource-constrained embedded systems used in power electronics and energy infrastructure. The research will investigate how machine learning
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, career events and professional development workshops, as well as a wide range of theoretical and practical courses at both the FMI and the University of Basel. Since 2016, we also offer an MD-PhD Program
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training at a higher education institution in the scientific areas indicated above, with the aim of consolidating their scientific training through the development of research work, whether or not integrated
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for science, creativity and development. Therefore, we welcome applications from people with diverse backgrounds and perspectives. URL to this page https://web103.reachmee.com/ext/I017/1114/main?site=7
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
, reference no. 2023.18249.ICDT, financed by national funds through FCT/MCTES (PIDDAC Workplan: Development of methodologies and machine learning algorithms for the detection of anomalous behaviors in flow rate