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(including tools such as Quantum ATK or VASP etc.). d) Condensed matter physics. Knowledge or experience in at least one of the following topics: e) AI algorithms and deep neural networks (including deep
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the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics its processing capabilities but also its adaptability, leveraging early
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identification of biological sounds using passive acoustic data. Passive acoustic monitoring will be conducted with species identification based on a neural network trained and tuned to the turbulent waters
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, accurately and securely. Goal of this PhD project High-capacity neural models, such as transformers, have been pivotal for establishing general-purpose models for a wide variety of natural language tasks
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skills in one or more languages (Python, C/C++, or others) experience in mechanical testing profound knowledge of machine learning methods (e.g., neural networks, Gaussian processes, active learning
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., neural networks, Gaussian processes, active learning) interest in materials science (e.g., SCC) excellent knowledge of English (written and spoken) high degree of motivation, creativity, and flexibility
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architectures and principles from Bayesian neural networks and biological sequence models, including large DNA and protein language models. The project also aims to develop a prototype federated learning
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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interaction networks that contribute to the pathogenesis of these diseases. This is a full-time, non-tenure-track position working in the Laboratory of Molecular Therapeutics. The appointment is annually
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-edge solutions and pushing the boundaries in the field Develop advanced artificial neural networks (ANN), including training, mapping, and weight quantization Collaborate with cross-functional teams