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with specialization in cognitive science, psychological methods or a related discipline. Extensive experience coding in R and Python (or related computer programming languages). Excellent written and
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recent years in conjunction with Variational Monte Carlo methods and efficient optimization techniques to obtain excellent representations of the ground state of many-body quantum systems
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inequalities? Are you interested in working in an interdisciplinary and mixed-method team? We currently offer a PhD-project on the political economy of housing and health within the broader DWELLWELL project
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, aiming at improving the information extraction and the of icy planetary bodies subsurface by radar sounder data processing. The selected candidate will be expected to develop novel machine learning methods
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present. Although methods exist to balance early diagnosis benefits and false positive risks for single disease tests, such methods are not available for multi-disease tests. In the MERIT project, we will
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information gain while minimizing testing hours to ensure these new technologies are reliable, sustainable, and affordable. Key Responsibilities Research & Development: Develop algorithms to estimate survival
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. Desirable Criteria Experience implementing machine learning or deep learning models (e.g., neural networks, probabilistic learning methods). Knowledge of state estimation techniques, such as Kalman filters
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be co-supervised by a researcher from Sorbonne University (regarding the computational method development) and a researcher from the University of Melbourne (regarding the application of the new
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systematically improve the quality of production processes and final products. Continuous improvement must be implemented as a managed and ongoing system supported by modern quality management methods and computer
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to receiving your application! Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and