30 bayesian-object-detection Postdoctoral research jobs at Aalborg University in Denmark
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the ERC Starting Grant research project “Exploiting Nanopore sequencing to discover what microbes eat (NanoEat)” with the aim to combine state-of-the-art metagenome sequencing with state-of-the-art data
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uncertainty from climate projections into land-use forecasts. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models
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has a strong background in control engineering, with documented expertise in optimal control, adaptive control and online optimization, stochastic systems, Bayesian inference, and state estimation and
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theory, physics, mathematics, computer science, and statistics. This Postdoc position falls under Research Thrust RT4 on Reliability and Trustworthiness. The objective is to explore and address research
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with focus on reaching a shared objective, and to achieve a good work-life balance by managing the demands of an ambitious career alongside personal well-being, hobbies, and family time. In terms
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services, aiming for maximum resilience. The Postdoc will focus on the following key research objectives: Create a framework for analysing and designing satellite system solutions in cases involving Danish
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monitoring scientific progress and ensuring that project objectives and milestones are met. Your competencies The candidate must have a strong background in control theory, reinforcement learning, and game
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tasks You will join the Grand Solution project 'DRONES: Drone-Obtained Electromagnetic Signatures' to exploore innovative approaches such as drone-based radio testing for large objects and EM signiture
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MOFs and their hybrid materials. The primary objective is to explore the fundamental structure–property relationships that govern MOF vitrification and liquid-phase behavior, and to develop new MOF-based
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF