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field. Have proven expertise in statistical modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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) 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 based on quantum phenomena
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data from major facilities, including NASA’s Kepler, TESS, and JWST missions; ESA’s Gaia mission; and large-scale spectroscopic surveys such as LAMOST. Experience working with large, complex datasets is
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an advanced AI-augmented digital platform (AiCT-Med) powered by cutting edge machine learning models trained on multiple large, aged care datasets from providers across Australia. The platform is designed
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motivated candidate to carry out bioinformatic analysis on large genomic datasets, with comparisons to associated metadata. This will include development of analysis pipelines and interpretation of whole
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will research novel methods for effectively working with geometry models of large and complex assemblies in HPC environments to support high-fidelity engineering simulations (e.g. FEA and CFD). This post
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that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging,” and we love
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Python – information provided in the CV and/or motivation letter; c) Processing and visualization of large files (NetCDF) – information provided in the CV and/or motivation letter. Contracting requirements