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findings to military stakeholders and the implementation of evidence-based practices within military medical populations. Therefore, applicants should have experience working with, or significant interest in
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satisfactory performance and availability of funding. Research topics of interest include numerical methods for scientific machine learning and AI, and their applications to various science and engineering
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | about 4 hours ago
, the relation between human cognition and machine learning, and others. The position is offered for three years. The starting date is, in principle, flexible, while we aim to get started as soon as possible
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-principles and atomistic simulations with machine-learned interatomic potentials to: Model reaction pathways on metal-oxide surface, including adsorption, reactions and diffusion steps. Construct atomistic
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are proficiency in Python, deep learning frameworks such as Keras, PyTorch, TensorFlow, or other related software stacks, and a solid background in machine learning, cybersecurity, or AI robotics, and the ability
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of faculty at SUNY Polytechnic Institute and the University of South Florida, consisting of mathematicians, physicists, computer scientists, and engineers investigating applications of deep learning
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, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate will design and implement differential privacy
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& Machine Learning not excluding other modeling frameworks) of safety critical socio-technical infrastructure systems. The candidate will be primarily responsible for writing and submitting refereed journal
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environment The Brain Imaging & Neuro Epidemiology group (BraINE) develops advanced methods for medical images analysis, combining computer vision, radiomics and deep learning approaches. The team has a double
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: What are efficient machine learning strategies to identify large ensembles of nanoparticles in tomograms (i.e., to identify nanoparticles on irregular 2D surfaces in 3D space)? What are appropriate