8 coding-"EPIC"-"EPIC" Postdoctoral scholarships at Technical University of Munich in Germany
-
the project include mathematical derivation, analysis, and comparison of models, methods, and simulation approaches; rapid prototyping of new ideas in custom code; implementation of new models, methods, and
-
methods (LBM). For fluid simulations, we utilize the high-performance LBM framework waLBerla, predominantly written in C++, but increasingly adapted for GPU computations through automatic code generation
-
., for convergence, existence, and uniqueness of solutions Fast prototyping of new ideas in individual code Implementation of new models, methods, and algorithms into an existing framework, with a focus on efficiency
-
• 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
-
++ 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
-
++ 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
-
++ 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
-
- 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