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to stay at the forefront of medical science, and educators to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater
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Michael Bronstein, AITHYRA Scientific Director AI and Honorary Professor of the Technical University of Vienna in collaboration with Ismail Ilkan Ceylan, expert in graph machine learning, invites
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interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms
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hired for this position will bring expertise in advanced quantitative approaches, including ecological or evolutionary modeling, genomics, or advanced computation (e.g., machine learning, deep learning
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research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong communication skills in English and good knowledge of French
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
PhD supervisors and co-direction Name: GAUCI Surname: Marc-Olivier Grade: HDR Institution: ICARE, Inserm U1091 Email: gauci.mo@chu-nice.fr Phone number: 04 92 03 70 27 Name: Micicoi Surname
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team, your expertise in AI and other cognitive computing methodologies, such as but not limited to machine learning (ML), large language models (LLMs), small language models (SLMs), natural
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of the candidate), in visualization and data analysis, cooperative systems, data mining and machine learning, education, didactics and entertainment computing, or Neuroinformatics. Across faculties, renowned
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image