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the context of our commitments to the ATLAS Experiment at the CERN Large Hadron Collider. This will involve undertaking specified activities in the operation, performance-optimisation and exploitation
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. Working closely with the ABI program’s leadership team, you’ll contribute to data curation, protocol development, predictive modelling, and novel analytics for large-scale neurocritical care datasets. As
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Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | 24 days ago
in forestry. Specifically, the candidate will be responsible for: Performing and leading data collection with UAVs for the ISR team within the ForestSphere project; Developing a UAV-derived large-scale
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5 Sep 2025 Job Information Organisation/Company CNRS Department Architecture et Réactivité de l'ARN Research Field Biological sciences Medical sciences Pharmacological sciences Researcher Profile
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. Thanks to feedback from our employees over the years, we’ve been fortunate to be named a top employer around the world. Alnylam is extremely proud to have been recognized as the #1 Large Employer by Boston
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artificial intelligence Experience with genetics and genomic data Experience with large, diverse datasets and data mining approaches Proficiency in Linux and computational programming Strong computational and
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queries, and dashboards Familiarity with (biomedical) image processing Familiarity with processing data collected using wearable devices (biomedical) Experience with natural language processing and Large
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agentic architecture. With prior experience in AI security and AI agents, including prompt injections, data extraction, jailbreaking, poisoning and adversarial attacks, the candidate brings transferable
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survivor engagement in focus countries: the UK, South Africa, and Kenya. The study adopts a mixed-methods approach, combining systematic evidence review, law and policy analysis, secondary data analysis, key
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learning / computer vision/ human behavior modeling, with specialization in one or more of the following areas:, supervised/unsupervised/self-supervised learning, large vision models, multimodal foundation