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Application deadline: 30/04/2026 Research theme: Nuclear Engineering How to apply: https://uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded; home students are eligible to apply
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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within the Norwegian Center on AI for Decision (aiD), benefiting from broad and divers expertise, and strong industrial connections. The project will have theoretical and algorithmic developments, software
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mentoring for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz-juelich.de/en
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of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in developing methods to quantify uncertainty
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collaborators. Tasks include formulating optimisation problems, developing algorithms for optimisation with Bayesian models, and implementing solutions in relevant software. Further tasks include the formulation
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Technology, Dep. ETI / Embedded Systems, we are looking for a researcher as of the 01.04.2026. Your tasks: Development of architectures and algorithms for adaptation of time-triggered systems based
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. Expected Work: The selected candidate will conduct research at the intersection of wireless communications, signal processing, and control theory, aiming to develop cutting-edge algorithms for joint
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for expensive new dispatchable generation capacity, enable deeper renewable energy penetration, mitigate grid congestion, and reducing CO₂ emissions at national scale. In this PhD project, you will develop