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information, please visit the Computational Imaging group page: www.cwi.nl/en/groups/computational-imaging Where to apply Website https://www.academictransfer.com/en/jobs/363520/phd-student-on-the-subject-of-i
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
into resources that can be used for machine learning. The PhD will therefore investigate multimodal approaches that connect visual sign-language information with textual representations under low-resource
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flow theory or machine learning frameworks (e.g., PyTorch, TensorFlow). Strong written and oral communication skills in English. Personal characteristics To complete a doctoral degree (PhD), it is
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31.07.2026, Academic staff We are seeking a researcher in Scientific Machine Learning (SciML) to join the project "Data science at scale" at the Technical University of Munich, Germany. Ideal
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(meta-)genomes Experience in the computer-assisted analysis of large biological datasets (e.g., using R, Python, and Bash/Linux environments) Very good written and spoken English skills Ability to work
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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | about 2 months ago
for a PhD student to join a project at the interface of biomolecular dynamics and modern data science (ERBIOM project). Our group has a long-standing track record in molecular modeling, molecular dynamics
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
applications will be tackled. The first concerns electrical machines like power plant alternators for which EDF has developped numerical simulators and has large sets of sensor data (measuring leaking flux
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15 Aug 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Programming Engineering » Computer engineering Engineering » Electrical
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-wide traffic prediction Design physically consistent and interpretable machine-learning methods for dynamic traffic systems Test and validate prediction models using large-scale real-world traffic data
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field. Strong foundations in machine learning and familiarity with current AI tools and practices. A solid understanding of large language models, in particular their reliability, security, and