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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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, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab , the 6GSPACE Lab , the HybridNetLab
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, REQUIRED EDUCATION LEVEL, PROFESSIONAL SKILLS, OTHER RESEARCH REQUIREMENTS PhD in Mathematics or Computer science, A good understanding of BFT ; Ability to link technical problems and algorithms, graphs
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systems onto real robots for tasks such as tracking, 3D reconstruction, object recognition, and visual SLAM. They will be working with a team composed of PhD students, Research Assistants, and Postdocs
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. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills include: Strong foundation in one of the following areas: Machine Learning / Information Retrieval
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must be within five years of receipt of their PhD to be considered for initial appointments and subsequent renewals. About the School of Mathematical and Statistical Sciences (SoMSS) SoMSS currently has
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create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train
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internal reports and manuscripts. Requirements: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related. Solid knowledge of machine learning, including graph neural
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) Social Media Analysis (iii) Algorithmic Privacy, (iv) Analysis of Academic Collaborations, (v) Human-Bot interaction, (vi) Network Science. The ideal candidate is self-motivated and hard-working with a PhD
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relevant expertise: A PhD in Computer Science or a closely related field, with specialization in Quantum computing and Graph theory In this role, you will be responsible for conducting research on graph