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for Quantum Technologies (CQT) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices
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of the project is to provide a timely update and modifications of this model, as new science and methods have evolved since its development. Learning Objectives: The selected fellow in this project will have the
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of algorithms Ability to design, implement, and execute empirical studies, General fluency in machine learning methodology, Joining the CMU team opens the door to an array of exceptional benefits, available
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Details Title Postdoctoral Fellow in Deep Learning Theory and/or Theoretical Neuroscience School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position
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learning technologies. The CNS’s ongoing projects focus on virtual humans and advancing simulation science-based theories and concepts in social and clinical education. Interests in extended reality
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or more of the following empirical research methods will be considered an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the
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Econometrics Virtual power plants Power systems and/or power electronics Machine learning Renewable energy systems Advanced statistics Language requirement: Good oral and written communication skills in English
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Health, Environmental Health, Biological Sciences, Biostatistics, Data Science, preferably with relevant experience. Prior experience with machine learning is a plus. Recruitment is open immediately and
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quantitative data analysis: applied machine learning, statistical analysis, and handling complex data. Programming skills in Python and R are essential Experience in applying computational methods to research
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one of the following: Econometric methods for causal inference; Data science and machine learning; Survey design and analysis; Qualitative analysis skills specialized in policy and geopolitics A good