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pursue an international academic career and contribute to the international research community through high-quality publications. The recruitment of PhD candidates is an important element of the
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, recent studies have demonstrated the limitations of current ground- and satellite-based observational networks. The PhD project aims for a new method to derive ground-level concentrations from satellite
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understanding of reinforcement learning foundations, with the ability to perform convergence and finite-sample analysis of complex, non-linear continuous control algorithms. Implementation Expertise
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are different, and no method can currently tell them apart. This project builds one — with consequences for how carbon inequality is measured, and for a new kind of demand-side climate policy. About
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PULSE, a generative (VAE) method revolutionizing predictions for disordered materials. You'll improve its accuracy, uncertainty quantification, and transition to a continuous latent space within a CEA
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knowledge-driven AI method for understanding the interaction between solid and fluid interaction. The selected RE is required to: • Developing a novel knowledge-driven AI framework for implementing
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sign problem theory, Quantum Monte Carlo method, DMRG, and machine learning Appointments of postdoctoral fellowship positions are offered for an initial period of two years, with the possibility of
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applications and algorithms that can leverage associative memories, including machine learning and LLMs, genomics, and classical data science methods (tree models, decision trees, finite automata). We
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to accelerate parts of the workflow. The project will involve method development, implementation, and application to molecular benchmark systems. You will work with quantum-chemical calculations
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Postdoctoral Fellow with Professor Morgane Austern. Professor Austern’s group focuses on research in high-dimensional statistics, probability theory, machine learning theory, graph data, Stein method, ergodic