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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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-learning architectures for sequential data (e.g., Transformers, graph neural networks, state-space models). Experience with OpenCV, GPU-accelerated inference, Docker, and modern software engineering
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with the goal of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and
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apply machine learning and deep learning models (e.g., graph neural networks, generative models, transfer learning) for materials property prediction, interpretation, and inverse design. Perform high
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on theoretical and computational aspects of quantum many-body systems, including Tensor Networks, Neural Quantum States, Stabilizer formalism, Complexity measures such as entanglement and quantum magic, quantum
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an international police clearance check may form part of the selection process. Project: The role of early-life microbiome in sculpting stress-social neural circuits in zebrafish For an information package including
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to identify and validate causal mechanisms linking microbial states to host physiology, brain function and behaviour. They will investigate how microbial, immune, endocrine, circadian and neural systems
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Ref. 4364_All. 3 - Methods and Tools for Secure and Autonomous Brain-Inspired Cyber-Physical Systems
. The neuromorphic component will address the design, optimization and deployment of Spiking Neural Networks (SNNs) and event-based algorithms on embedded processors and specialized accelerators, including data from
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and qualifications Expertise in advanced machine learning, deep learning and image vision techniques with focus on EO data (e.g. deep convolutional neural networks, transformers, deep learning based
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. The position in Heilbronn is already filled. This job description is for a position in Garching . Here, you will develop general-purpose, scalable linear solvers for training neural networks that represent