14 coding-"https:"-"FEMTO-ST"-"CSIC" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Postdoctoral scholarships at Technical University of Munich
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conducted in close collaboration with Everllence (formally known as MAN Energy Solutions). The developed methods have to be tested in simulation and on real engines. Previous Work https://openreview.net/pdf
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exploration. These methods will be developed together with the company CargoKite (https://cargokite.com/ ), which develops a ship for autonomous, highly flexible global container transportation. The transport
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finite elements) as well as alternative discretization methods (e.g., Lattice Boltzmann Methods), and high-performance computing. A selection of possible research areas can be found on our website: https
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also on power systems in the CoSES lab at the Technical University of Munich. Previous Work https://mediatum.ub.tum.de/doc/1731060/g5zgxaj96lcyhh8gh6le1xbuu.Wetzlinger-2023-TAC.pdf https
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) - Semantic 3D Scene Understanding - Face / Body Tracking, 3D Avatars - Non-Linear Optimization - Media Forensics / Fake News Detection How to Apply: Follow the instructions on our application platform: https
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++ coding skills • Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) • Enthusiasm and self-drive towards driving research forward :) How to Apply: • Required Documents: CV, research
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exercise solutions. [1] https://automata-tutor.model.in.tum.de/ [2] https://link.springer.com/chapter/10.1007%2F978-3-030-53291-8_1 Requirements: We are looking for highly motivated candidates who will fit
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the topic: 1. M Balaish, JLM Rupp, Widening the Range of Trackable Environmental and Health Pollutants for Li‐Garnet‐Based Sensors, Advanced Materials, 2021; https://doi.org/10.1002/adma.202100314 2. M
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• Integrated sensing and communication: fundamental limits and algorithm design (1 PhD, Mari Kobayashi, mari.kobayashi@tum.de) • Optical fiber channel modeling, receiver processing, and coding (1PhD, Gerhard
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- Proficient C++ coding skills (this is critical and will be tested) - Experience with deep learning frameworks (TensorFlow / PyTorch) - Excitement, self-motivation, and commitment to revolutionize the field