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Field
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develop and maintain the software for this shared demonstrator vehicle. Job requirements Completed (or about to complete) a MSc degree related to any of: artificial intelligence, machine learning
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methodological skills in both qualitative and quantitative research, including: Survey and interview methods. Focus groups and workshop facilitation. Experience with qualitative analysis software (e.g., Atlas.ti
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and the laboratory. You will be technically competent, and happy to develop your skills using a range of scientific equipment, measuring devices, and associated software. Some of the equipment commonly
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executable. This is a challenging research project at the intersection of AI, NLP, and software engineering, with applications in life sciences and beyond. We are looking for highly motivated applicants for a
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transferable skills such as HPC software development, extensive physical understanding of turbulent flows, and experience in modern ML architectures such as neural operators and transformers. The expected start
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, resulting in publications at top-tier international conferences and journals; Develop theory, implementations, and open-source software for hyperbolic deep learning; Collaborate with other PhD students and
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and fundamental areas. The candidate will develop transferable skills such as HPC software development, extensive physical understanding of turbulent flows, and experience in modern ML architectures
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publish their research in top journals in marketing as well as related fields. They deeply care about open science practices (e.g., data sharing and open-source software) and frequently host seminars
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of Prof. Frans Cornelissen at UMCG, as well as with the multidisciplinary project team comprising academics, clinicians, and software developers, to achieve the project’s objectives. The successful
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manufacturing technology for producing small to medium-sized thermoplastic composite components in high volumes. Process simulation software is being developed for virtual optimization of tool design and material