17 programming-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" research jobs in Australia
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. Skills Terms programming; R; Python; Statistical methods; machine learning; differential expression; bulk RNAseq; scRNAseq; Linux/unix; spatial transcriptomics URLs/references https://ramialison
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-Ouellette, S., & Rudzicz, F. (2021). BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data. Frontiers in human neuroscience . [2] https
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-Ouellette, S., & Rudzicz, F. (2021). BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data. Frontiers in human neuroscience . [2] https
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programming background with fundamentals in machine learning and data science. Experience in building visualisations and interactive immersive environments (using game engines like Unity3D) is
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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complexity. Proficiency in relevant scientific programming or quantum-software tools, such as Python, Julia, MATLAB, Mathematica, Qiskit, PennyLane or equivalent platforms. Experience mentoring or co
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maintenance and task planning. Required knowledge Stipend funding is available for domestic students only (Australian or New Zealand Citizens or Permanent Residents) Applicants should have strong programming
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computer programming background who has an interest in ecology and biodiversity conservation, or an ecologist with computational modelling experience (e.g., using R, Python, Matlab). Project funding
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two Magma Research Associates / Magma Research Fellows to develop and maintain the Magma computer algebra system (https://magma.maths.usyd.edu.au/magma/). These positions are based at the University of
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). Available at SSRN: https://ssrn.com/abstract=3461418 or http://dx.doi.org/10.2139/ssrn.3461418 Fitzgibbon, L.J., D. L. Dowe and F. Vahid (2004). Minimum Message Length Autoregressive Model Order