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, or similar, and a degree in Environmental Engineering, Environmental Science, or a related quantitative field. Position 2 will focus on large-scale data analytics and machine learning. Applicants should have
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for 3 years. The project is conducted in close collaboration with the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation
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intersection of machine learning and life sciences, developing next-generation models that improve our understanding of human biology and enable more proactive, personalized healthcare. As an Industrial PhD
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in dynamical systems modeling (ODEs) and machine learning and very strong programming skills (Java, Python). A background in evolutionary genomics research is a strong plus, as is previous experience
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in dynamical systems modeling (ODEs) and machine learning and very strong programming skills (Java, Python). A background in evolutionary genomics research is a strong plus, as is previous experience
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machine learning methods for detecting, classifying, and identifying wireless anomalies in real-world radio environments. You will design and experiment with AI-driven approaches for spectrum analysis, work
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for ethical AI. Integrate machine learning models, visualization dashboards, and backend services. Contribute to data collection, testing, documentation, and dissemination of open-source resources
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Models, Knowledge Graphs, and related fields (e.g., Graph Machine Learning) Tasks: scientific research in at least one of the following areas: Natural Language Processing, Knowledge Graphs, Machine
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Grant/funding reference: PID2023-149956OB-I00 Job title: Safe and efficient ports: comprehensive operational risk management through monitoring, advanced techniques and machine learning. PORT-AHEAD+AI
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of this data. The full content of the information clause of Article 13 RODO is available at https://www.ncbj.gov.pl/en/gdpr Website for additional job details https://www.ncbj.gov.pl/en/praca/postdoc-bp3518