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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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-traditional, e.g., event data) and network structures (for sensor networks). In this project, we will investigate Bayesian deep learning approaches to training models under uncertainty for several sensing
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with deep learning libraries (e.g., PyTorch) Ability to organise and prioritise work to meet deadlines with minimal supervision Strong written and verbal communication skills, with the ability to convey
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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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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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50 Faculty of Life Sciences Startdate: 01.08.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.07.2029 Reference no.: 4160 Explore and teach
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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