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chemical reaction networks with robotic systems and analytical science. You will also learn how to programme robotic systems and how to implement aspects of deep learning and neural networks for reservoir
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PhD: A deep dive into youth cyberhate Faculty: Faculty of Social and Behavioural Sciences Department: Education & Pedagogy Hours per week: 28 to 40 Application deadline: 5 September 2025 Apply
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. For this PhD position you will work on modelling the processes and feedbacks that couple the AMOC and polar ice sheets, with particular focus on sea ice and (North Atlantic) deep-water formation regions such as
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tomorrow’s living environments? And how can we support mutual learning between researchers in the geo-information sciences and societal actors when engaging with an increasingly uncertain and turbulent future
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for Sustainable Energy, researchers from academia and industry develop, implement and evaluate new deep reinforcement learning methodology to solve sustainable energy challenges. Key responsibilities The lab is
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models. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience a and strong deep learning programming skills. Ability to work in an
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of the processing system online. Our approach will be to draw on a broad selection of tools including (deep) reinforcement learning, queuing networks, online algorithms and systems engineering. In addition, a large
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internally, so while you learn the intricacies of our industry, you’ll have plenty of opportunities to contribute and directly affect our bottom line within your first few weeks on the team. While interest in
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simulations with deep learning neural networks and swarm robots, virtual reality experiments, animal communication research, and more. In a range of projects, we show that languages can effectively be seen as
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Organisation Job description Are you passionate about combining the directed evolution of diverse biomolecules with deep learning approaches and contributing to the development of better (bio