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the following ones. Exploration of active auditing techniques for large machine learning models, use of reinforcement learning, potential application to recommender systems. The PhD will mainly investigate
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that can be run. Emulating expensive processes could allow more data to be generated from better models, at lower cost. The central science question is: how can machine learning and evolutionary computation
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characterize the spatio-temporal contexts that favor crises. • Development of advanced predictive models (multivariate approaches, machine learning) combining event data, snow and weather data, and remote
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular
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challenging for classical computing architectures. Some of your responsibilities will include: Design and develop mixed-signal circuits for implementing ONNs. Modeling, simulate and benchmark different
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analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN implementation topology and its energy efficiency
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research
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machine learning for time series, geospatial data or dynamic models; ideally experience with deep learning frameworks (e.g., PyTorch). Strong analytical and conceptual skills for designing and interpreting
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. The research in the PhD project will focus on core spatio-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation
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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning