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the toxicity of degradation by-products. To be successful in this role, you will hold (or be near completion of) a PhD in chemistry, materials science, chemical engineering, or a related field. You will have
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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific
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science, machine learning, advanced computational design, and wearable technologies. To be successful you will need: Completion of a PhD in electrical, software, optical, biomedical engineering or physics
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Integrated Planning & Learning and Reinforcement Learning in non-deterministic and partially-observed scenarios. The methods will be evaluated on physical robots. The ideal candidate would have: A PhD (or
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-atomic potentials using a combination of classical and machine-learning (ML) approaches (and a new hybrid method recently developed in our group). Some of the types of simulations that will be performed
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, Machine Learning, and Big Data Analysis To Apply We encourage all candidates who meet the selection criteria to apply for this role. Please submit: A current CV A cover letter specifying whether you are
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, Machine Learning, and Big Data Analysis To Apply We encourage all candidates who meet the selection criteria to apply for this role. Please submit: A current CV A cover letter specifying whether you are
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degree with strong skills in programming and machine learning. Please contact Zhuang Li for more information. The project focuses on developing multilingual datasets and advanced methods to detect and
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This project is aimed at developing platforms to provide security in the post-quantum era. The project aims to incorporate quantum technologies, including quantum machine learning and quantum
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with leading experts in the field. Applicants should have a strong background in machine learning, graph-based methods, and an interest in causal learning. Scholarships are awarded based on academic