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quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software package Good communication skills in
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strong publication history, including but not limited to conferences such as MICCAI, NeurIPS, ISBI, ICCV, ICML, ECCV, or others. Fluent familiarity with at least one coding language for ML or data analysis
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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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, methods, and algorithms into existing high-performance frameworks, the fast prototyping of new ideas in individual code, an interest in the entire simulation pipeline: starting from simple algorithms
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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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++ 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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++ 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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- 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