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for Research Staff Development for more information. About You To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in
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diverse data sets, applying advanced analytics, and leveraging ML/AI techniques to detect, quantify, and forecast global risks affecting sourcing strategies. It will also include assessing AI-driven demand
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of Excellence aspires to actively contribute to the European Research Area (ERA) priorities in Atmosphere and Climate, Resilient Societies and Big Earth Data Analytics, as well as to become the reference Earth
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methods, leveraging digital twins, data analytics, and reliability engineering. In parallel, the role includes project oversight responsibilities, supporting effective coordination of consortium activities
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segmentation for AI model validation and QA Integration of data across AMD and DR projects to support shared analytic frameworks, reflecting a systems-level approach to retinal disease mechanisms. EZ band
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publications. Qualifications Required Education and Experience: PhD degree in any of the following: plant biology, plant physiology, analytical chemistry, genetics, biotechnology, food science, or other closely
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profile PhD in Electrical Engineering, Computer Science, Applied Mathematics, or a closely related fieldStrong research track record, preferably with publications in leading AI and Computer Vision
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refinement. Publish results in peer-reviewed journals and present findings at international conferences Required Qualifications PhD in proteomics, analytical chemistry, physical chemistry, or a closely related
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pillars such as Big Data Analytics and Management, Machine Learning and Optimization, AI for Data Science, Deep Learning, Generative Learning, Biometrics Processing, Natural Language Processing, Computer
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microbiological and analytical techniques including isolation of quorum-sensing-bacteria, design of RNA FISH probes, high-throughput testing on microbial cultures, analytical tools such as confocal microscopy, flow