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- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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bioinformatic workflows. Familiarity with biomedical ontologies and text mining on Electronic Health Records and biomedical literature Knowledge of machine learning / deep learning with an interest in
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, e.g. experience fitting Reinforcement Learning models or applying Agent Based Modelling to human behavioural data. You should have a deep understanding of the strengths and limitations
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successful candidate will possess skills in natural language processing and deep learning. Experience of studying the robustness and generalisability of LLM would be beneficial. This is a full time post (35
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/C++; hands-on experience with deep learning libraries (e.g., PyTorch) 5. Ability to organise and prioritise work to meet deadlines with minimal supervision 6. Strong written and verbal
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assemblages and morphometrics, sedaDNA and the deep microbiological biosphere), as well as applying other dating techniques including radiocarbon, OSL and palaeomagnetics. In addition to having the opportunity
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SIT's mission is centred on nurturing industry-ready graduates who possess deep technical expertise and transferable skills to address future challenges. We collaborate with industry in our
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SIT's mission is centred on nurturing industry-ready graduates who possess deep technical expertise and transferable skills to address future challenges. We collaborate with industry in our
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on the training strategies. In this project, we will investigate Bayesian methods to train deterministic SNNs (with deterministic activation functions) or probabilistic SNNs. Bayesian deep learning methods have
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discipline. The candidates will have expertise in computational imaging, with: (i) an algorithmic focus, with particular interest in methods at the interface of deep learning and optimisation theory, and/or