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selection and validation, supervised and unsupervised learning, optimization techniques, (deep) neural networks, probabilistic methods and statistics, data visualization, natural language processing
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on developing novel neural network approaches to predict protein conformational dynamics from fixed protein structures, addressing fundamental challenges in structural biology with broad applications in
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our understanding of the neural code of cognition but also inspire novel strategies for the treatment of psychiatric disorders characterized by working memory deficits. Summary of the project: https
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of network connectivity, synapses, and ion channels. The team currently focuses on the neural basis of navigation behavior in Drosophila , combining electrophysiology and optical physiology in behaving
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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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Control group investigates the neural mechanisms of literacy by treating the human visual system as a complex computational gateway that links sensory input with linguistic processing. By leveraging
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
., Hitzler, P., Bianchi, F., Ebrahimi, M., & Sarker, M. K. (2020). Neural-symbolic integration and the Semantic Web. https://doi.org/10.3233/SW-190368 [5] Jradeh, C. K., Raoufi, E., David, J., Larmande, P
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modelling, or live neural imaging is desirable Experience working with neurons and knowledge in neurobiology is desirable Track record of international mobility is highly valued Publication record is
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strives to advance understanding of brain systems that play a role in regulating emotions and vulnerabilities in these neural networks that can contribute to risk of child and adolescent mental health. Our