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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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. Create predictive algorithms for the occurrence of cyanobacteria blooms; 3. Support field activities, process large volumes of data, and contribute to scientific publications. Requirements: • PhD in areas
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want to hear from you! Your Job: Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant
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, Oslo. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/291053/phd-research-fellow-in-mathematics Where to apply Website https://www.jobbnorge.no/en/available-jobs/job
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Your Job: In this position, you will be an active member of the SDL “Fluids & Solids Engineering” and will collaborate strongly with the SDL “Applied Machine Learning”. You will have the following
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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have: A PhD (or equivalent) in a relevant discipline (e.g., biostatistics, machine learning, computer science, clinical informatics, natural language processing). Strong skills in data analysis and
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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at: www.fz-juelich.de/gp/Careers_Docs Further information on doctoral degrees at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd We
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. The research in the PhD project will focus on core spatio-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation