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methods to simulate between functional chemically active surfaces and molecules/liquids. Central methodologies include: static DFT calculations; TBMD and AIMD; classical atomistic and coarse-grained
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of the sea, with a focus on questions related to marine protected areas About the position You will primarily work on developing and applying video-based methods for monitoring fish in protected areas and
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. Your profile You have documented expertise in marine ecology and computer vision and machine learning methods for video-based fish monitoring. You have excellent IT skills and experience in handling
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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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on food safety. The researcher will be responsible for planning and conducting field sampling and laboratory assays, including the development and validation of multiresidue methods by liquid chromatography
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coherence lifetimes for the solid state, and the ability to leverage the advanced nanofabrication methods of the semiconductor industry. The selected candidate will join the Quantum Hardware group lead by
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(Governmental Public Employment Portal), as well as in both Portuguese and English in the Apply UC computer platform and in the EURAXESS Portugal Portal, at https://www.euraxess.pt/ . Pursuant to paragraph h
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studies and interactive AI systems. This position will be funded based on an initial 2-year contract + 2 years extension. The key idea is to apply theories, models, and methods from psychology to improve
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The application form and agreement including an acknowledgement about providing personal data are available for download below on this page http://www.faf.cuni.cz . The estimated monthly wage: 62 000 CZK (1,0 FTE