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thereafter. Explaining complex AI models is a key challenge for ethically responsible AI. Explainable AI (XAI) research aims to provide relevant information to assist developers and users in analyzing AI
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molecular experiments for hypothesis-driven research Analyzes, interprets, summarizes and compiles data Present research data at lab meetings, scientific conferences, and in peer-reviewed publications under
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the UCD School of Mathematics and Statistics. The successful candidate will lead research focused on developing a scalable, AI-driven quality control (QC) system for synoptic and climate observation data
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mainly be connected to DRIVE PR, but may also be linked to related projects within data-driven product realisation, digital engineering, systems engineering, geometry assurance, automation, or model-based
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Potsdam-Institut für Klimafolgenforschung e.V. (PIK) | Potsdam, Brandenburg | Germany | about 2 months ago
of integrated assessment and political futures modelling, starting on 01.11.2026. The position is funded for 2 years and 2 month until 31.12.2028. Renumeration is in accordance with the German public tariff
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immunology, AI-driven discovery, and next-generation therapeutic development. Our lab studies how tumors interact with the immune system and develops new ways to interrogate and reprogram those interactions
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-driven science and Cornell University’s second largest college. We work across disciplines to tackle the challenges of our time through world-renowned research, education, and outreach. The questions we
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Challenge: Predict long-term cardiac growth and remodeling in cardiovascular disease. Change: Develop multi-scale mechanobiological models for virtual human twins. Impact: Advance patient-specific
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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | 2 months ago
a postdoctoral researcher fully focused on artificial intelligence in the life sciences. The role centers on working with foundation models for proteins and DNA/genomic sequences, and on overseeing
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics