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synthetic organic and medicinal chemistry are encouraged to apply. The research is aimed at developing an automated chemical platform for the synthesis and biological evaluation of natural products as leads
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applied to the study of sites, particularly rock schematic rock art sites of southern France. The contract will be carried out in the ANR SCHEMA project (https://schema.hypotheses.org/a-propos ). ANR SCHEMA
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Lab, to begin in August 2026. This position is funded by the Andrew W. Mellon Foundation as part of a grant supporting the development and outreach of open-source technology for applying AI methods
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new insights into the phenomena observed and enrich the databases required for deep learning methods. The neural networks currently being developed at LISTIC to detect and segment areas of movement in
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cybersecurity to join the FrostShield research project, funded by Rannis. The position focuses on developing advanced, AI-supported cyber defence solutions tailored to the needs of small and medium sized
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago
. Description: This is an opportunity to conduct independent research on our cosmic origins. Areas of interest may include, but are not limited to, the evolution of galaxies: dwarf galaxies, high-redshift
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. The successful candidate will be joining the Optoelectronics group led by Prof. Dr. Valerio Pruneri. The successful candidate will be responsible for the development of quantum communication devices, systems and
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of land use and climate change on the ecohydrological balance and, consequently, on water security. Activities: The activities involve the development and analysis of environmental, climatic, and land-use
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for Nanoscience & Nanotechnology, has developed a strong expertise in harnessing light-matter interaction at the most fundamental level. We develop crucial resources for optical quantum technologies, including high
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surveillance and preparedness planning using multiple modeling approaches. The successful candidate will develop and implement statistical and machine-learning models, integrate multi-source ecological datasets