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Field
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modeling with deep learning for the analysis of hyperspectral imaging data. The researcher will be responsible for the design and development of numerical models, including neural network architectures
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modulation, radar/sonar signal processing, and machine and deep learning. WORK PERFORMING: Individual will perform research generally in the area of statistical signal and array processing. Topics of specific
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 15 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 | 11 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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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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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