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tracking and autoencoders for amplitude and phase noise characterization Bayesian filtering Building experimental set-ups for noise characterization Reinforcement learning strategies for comb generation
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focus on the following areas: Subspace tracking and autoencoders for amplitude and phase noise characterization Bayesian filtering Building experimental set-ups for noise characterization Reinforcement
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the team. Managing own goals, objectives and KPIs. Works within the team with impact across teams. Manages own competencies and job requirements. Responsible for own capabilities and addresses any gaps in
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on academic qualifications, research potential, and their ability to contribute to both the scientific and industrial objectives of the project. We offer DTU is a leading technical university globally
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. This objective will be achieved through a structured research training programme consisting of original individual research projects and education in technical and transferable skills. Experts from 11 doctoral
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missions: research, training, management and innovation. This objective will be achieved through a structured research training programme consisting of original individual research projects and education in
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objective of this PhD position is to advance research in statistical signal processing and machine learning for microphone array data, with a focus on sensing under uncertainty. The successful candidate will
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the project from conception through to publication, ensuring adherence to scientific and funding objectives. Student Supervision: Guide and support students' research, promoting their academic growth and
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validated in half-cells and full working batteries at industrial partners at TRL 6. Our objectives: Multiscale modelling to better understand RFB behavior and identify optimal hierarchical shaped pore- and
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one main research objective, which is to study the neuro-inflammatory response that occurs following ischemic stroke with the aim of contributing to the development of novel therapies to improve outcome