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“HORIA HULUBEI” National Institute for Research and Development in Physics and Nuclear Engineering | Romania | about 1 month ago
) announces a vacancy notice for an Doctoral research assistant position within the Project PCE 65 - „Magnetic resonance methods for new observation timescales in the detection of radiation dose-rate response
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, you will develop innovative small area estimation methods to produce high-quality composite SDG indicators, combining survey, census, and non-traditional data sources such as web and satellite data
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computational challenges. This PhD project will investigate novel registration strategies for ultrasound-derived musculoskeletal point clouds. The work will focus on developing geometry-aware alignment methods
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Your responsibilities: As a University assistant, you will contribute to the work group Machine Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods
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with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from
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11 Mar 2026 Job Information Organisation/Company cellumation GmbH Department HR Research Field Engineering » Computer engineering Engineering » Mechanical engineering Researcher Profile First Stage
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PhD Scholarship PhD Opportunity in error correction codes for free-space quantum communications. This includes new analysis, design and decoding methods for error correction codes for information
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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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) Master's degree in a socio-technical programme, such as: (Applied) Data Science, Econometrics, Artificial Intelligence, (Computational) Social Science, Human Computer Interaction. Experience with at least
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research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and