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Field
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) simulations will also be performed for the investigations. Furthermore, machine learning can be tested to accelerate MD simulations. In this project, you will be responsible for the following tasks in
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, and the mathematical and computational foundations of neural networks. Familiarity with the following areas is meritorious: machine learning, computational complexity, tree automata and tree
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cell (and one cell–cell interaction) at a time. You will work with large-scale single-cell and spatial transcriptomics data to develop and apply single-cell foundation models — generative machine
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, numerical methods, or machine learning approaches is an advantage. Fluent command of written and spoken English is necessary; German is an advantage but not required. High degree of independence, motivation
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modeling and computational workflows Knowledge about machine learning: statistics and deep learning Experience in data analysis, visualization and presentation Good programming skills in languages such as
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identification and machine learning. The key challenge is striking a balance between, on the one hand, modelling the physical, dynamic and nonlinear behavior of the components with sufficient physical accuracy
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enhance real-time decision-making in road traffic management. The project aims to bridge the gap between recent advances in AI and machine learning, in particular, multimodal and instruction-tuned
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contribute to the design and development of Machine Vision approaches for the quantitative analysis and phenotyping of agricultural systems: Training/Development of computational models for the quantitative
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, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong programming skills (Python/C++); Proven interest in generative models
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, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong programming skills (Python/C++); Proven interest in generative models