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/Qualifications PhD in Computer Science or related field (with preferred specialization in Machine Learning/Deep Learning); Documented experience in Machine learning and Deep neural network model design and
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the quality of reconstructed physics objects towards a 4D global event reconstruction. The work will include the usage of Machine Learning techniques to boost the performance gain and will focus on one
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computing, HPC infrastructures, and machine learning. Hicrest Laboratory combines expertise in parallel algorithms and high-performance computing with reliable computing systems by combining a hardware
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marker-less motion capture • Knowledge of machine learning methods • Good communication skills • Strong problem solving attitude • High motivation to learn • Spirit of innovation and
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artificial intelligence and machine learning. The software will be tested exploiting existing HI data for ~1000 galaxies and new HI data from ongoing surveys with SKA pathfinders (ASKAP and MeerKAT
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should have expertise in statistics, programming, and the analysis of cancer omics data. Interest in network biology and knowledge of data science techniques such as machine learning and being familiar
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data (maximum 20 points); Approaches for the statistical modelling of microbiomes, including meta-analytical and machine-learning methods (maximum 20 points); Computational methods for functional