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Experience with deep learning for image analysis and/or medical image processing Knowledge of self-supervised learning, representation learning, and/or generative models Experience with multimodal machine
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) for general criteria for the position. Preferred selection criteria Experience or strong interest in one or more of the following areas is considered an advantage: Machine learning, deep learning, natural
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feedback control in microbial fermentation. Typical tasks include: AI for spectroscopy analytics: spectral pre-processing; chemometrics and ML (PLS baseline; modern ML/deep learning as appropriate); drift
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in English Solid knowledge in finite element analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks
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analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks on material design by using PyTorch or Matlab PLEASE
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at the time of application Special requirements for the position: possess solid programming skills (e.g., Python, R, GIT) familiarity with machine learning, data analytics, or deep learning keen interest in
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selection criteria Solid theoretical background in robot perception and navigation. Deep foundation in modern machine learning. Solid programming skills in C++ and Python. Experience with ROS is a plus
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for the position. Preferred selection criteria Solid theoretical background in robot perception and navigation. Deep foundation in modern machine learning. Solid programming skills in C++ and Python. Experience with
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Language Model-based application development. Knowledge Graph Development for Sensor Data. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial intelligence, machine