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⦁ Experience with CATIA and Python are advantageous What we offer We offer flexible working hours, excellent facilities and the opportunity to play an active role in shaping resource-saving manufacturing
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Knowledge in the field of Machine Learning, including training, inference, and optimisation of transformer architectures. Knowledge in the field of ML security is desirable. Good Python skills, especially
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mechanisms as well as the effectiveness and limitations of corresponding defense strategies. What you contribute Very good Python skills, which will be tested in the interview. Basic understanding of AI/ML
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) Familiar with basic terms and concepts such as: classification, hyperparameter optimization, fine-tuning, model evaluation Profound knowledge of Python is mandatory and will be tested in the interview
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-tuning, evaluation of models) Solid knowledge of Python is mandatory and will be tested in the interview Advantageous: ability to independently implement methods and procedures from scientific publications
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experience (Python, plant control) and knowledge of vacuum technology are a plus, but not required What we offer 👥 Team spirit: Creative and interdisciplinary working environment, highly motivated team
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, applied mathematics, or computer science Programming skills, ideally in Python, C++, or Fortran Knowledge of topics like fluid-structure interactions or monolithic/partitioned couplings or numerical methods
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programming skills, preferably in Python good language skills in German or English enjoy experimental and scientific work team player, open-minded and motivated to work independently and purposefully What you
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the solution by integrating state-of-the-art MARL methods, with a strong emphasis on scalability and reliability. What you contribute Experience with Python ML stack, e.g. TensorFlow, Stable-Baselines3 Strong
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for AML Pattern Detection Explainable AI for Investigator Support What you contribute Strong programming skills (Python) Solid foundations in machine learning Interest in NLP and LLMs, and/or graph-based