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Field
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technological change driven simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic, and human data, and a new emphasis on the importance
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: https://www.jobbnorge.no/en/available-jobs/job/294558/phd-research-fellow-in-deep-learning-for-imaging-of-marine-ecosystems Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294558/phd
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for light–matter interaction in hyperuniform disordered plasmonic structures, including electromagnetic modelling, optimisation of metal–dielectric–metal resonators, and physics-informed machine-learning
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strong sense of community & inclusion Enjoy a career that makes a difference by collaborating & learning from the best At UNSW, we pride ourselves on being a workplace where the best people come to do
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computational pipelines for multiplex imaging, spatial transcriptomics, single cell RNAseq, and multi-omics data integration. Lead graph-based network and machine learning analyses of tumor immune
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experience) in applied mathematics, physics or engineering, and strong, up-to-date specialist knowledge in analytical and numerical spray modelling and machine learning. Experience with OpenFOAM or similar CFD
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aims to improve electrodialysis (ED) for REE separation by developing advanced membranes and integrating AI-driven optimization techniques. By combining materials innovation with machine learning
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requirements PhD in Physics, Applied Mathematics, Computational Science, or a related field Strong background in machine learning, particularly in the development and application of neural networks
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a PhD in machine learning, math, stats, physics, or some other technical area by the time the position starts. Additional Qualifications Candidates should have significant experience in some area of
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working with machine learning techniques to develop emulators for the theoretical predictions of various observables as function of cosmological parameters. The candidate will develop and use skills in