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algebra, topology, geometry and convexity Ohad Noy Feldheim Probability, Gaussian processes, discrete probability, extremal combinatorics Zlil Sela Geometric group theory, model theory Alexander Sodin
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Model. Int. J. Hydrog. Energy 2014, 39 (9), 4516–4530. https://doi.org/10.1016/j.ijhydene.2014.01.036. ; [3] Carral, C.; Mele, P. Modeling the Original and Cyclic Compression Behavior of Non-Woven
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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | 5 days ago
, 060024, https://doi.org/10.1063/5.0202322. Varsha R. Talanki, Qi Peng PhD , Stephanie B. Shamir MD , Steven H. Baete , Timothy Q. Duong , Nicole Wake. Three-Dimensional Printed Anatomic Models Derived
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 2 months ago
within protein-nucleic acid complexes. Journal of Chemical Theory and Computation. [3] Mokhtari, O., Grudinin, S., Karami, Y., & Khakzad, H. (2025). DynamicGT: a dynamic-aware geometric transformer model
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-time postdoctoral grant in Probability and Statistical Physics - CY Cergy Paris University Mathematical modelling of complex systems often involves combining deterministic structures with probabilistic
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. At present there is specific interest in advanced 3D perception techniques such as geometric foundation models, implicit neural rendering (NeRF, Gaussian Splatting) as well as semantic mapping. Our research
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. TCAD Sentaurus, Silvaco). Numerical analyzes will evaluate trade-offs between electrical performance of the power core and integrated functions, manufacturing parameters, and geometric parameters (e.g
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models, including options close to full-time ( https://go.fzj.de/near-full-time ), allow you to tailor your working hours to suit your individual needs FAIR REMUNERATION: Depending on your existing
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computational tools to capture and to analyze geometric urban data to answer important questions regarding cities. In particular, the following subjects will be considered: sidewalk representation, simulation
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg