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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 17 days ago
Molecular Dynamics, virtual screening, free energy calculations and Deep Learning), successful experimental collaboration experiences and excellent communication skills are preferred. Create a Job Match for
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 13 days ago
]. This requires interactively defining a template per flower, and is not suited to multi-layered petals, as in case of a rose. This postdoc position is concerned with a data-driven approach that learns
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical
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biological markers and state-of-the-art deep learning, the research will uncover conserved cellular state transitions and perturbation response programs across biological systems. The successful candidate will
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learning (RL) and deep reinforcement learning (DRL) for autonomous process management, dynamic resource distribution, and real-time decision-making. Design and deploy digital twins for integrated chemical
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operando data related to battery degradation and safety. You will develop and implement advanced deep learning models to analyse multi-modal operando data from accelerated stress testing, with the aim
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neuromodulation therapies such as deep brain stimulation. The team combines intracranial recordings and EEG, brain imaging, brain stimulation, modelling and advanced signal analysis to link neural dynamics
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partners, or translational research teams. Experience with Quarto, Python, and/or other programming languages. Experience and interest in data science or informatics education. Experience with deep learning
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Natural History. The researcher will develop deep learning models to predict individual bee age based on wing morphology. This model will be trained of existing wing images and applied to images of museum
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communication signals on our mental processes. What you will do Build novel deep learning architectures for auditory prediction (speech and/or music) prioritizing explainability and cognitive hierarchies Quantify