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or PhD in meteorology, atmospheric sciences, climate science or related field preferred. Experience in implementing machine learning methods in weather/climate research, analysis of dynamical model (e.g
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of research staff (contract type: open-ended contract; job category: assistant researcher) to collaborate with the funded line of research “Machine learning methods and models for acoustic and sound signals
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. The Opportunity: The successful candidate will focus on developing advanced machine learning and mathematical optimisation frameworks for energy system modelling, particularly under the growing presence of offshore
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dynamic functions of microbial communities. For this position, the major goal is to develop advanced computational modeling frameworks that combine physics and machine learning to predict, understand and
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learning, computational mathematics, and probabilistic modeling, with direct applications in medical imaging and beyond. Details can be found in the link below. The position is suitable for disabled persons
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information extraction. Relevant publications as an author in top-tier AI/NLP/ML conferences (e.g., ACL, EMNLP, AAAI). Proficient in programming languages and frameworks relevant to machine learning
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IoT and Machine Learning Security Engineer KTP Associate - INTERNAL ONLY Apply online Job number SST00289 School / Service School of Science & Technology Department Department of Computer Science
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participating in discussion forums Self-learn, experiment and evaluate new technical frameworks and technologies Qualifications Degree in computer science, machine learning, AI, and other relevant equivalent
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and modeling research. •Compile and analyze current scientific data on GHG emissions in freshwater ecosystems, focusing on CO2 and CH4 emissions. •Acquire, organize, and evaluate GHG emissions data from
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. The candidate must be able to communicate in English (oral and written). The knowledge of the French language is not required. The candidate must have a strong interest in machine learning. Skills in