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regions. Job description The research focuses on investigating/developing generic methods and algorithms in the context of multi-modal synthetic aperture radar (SAR) for the estimation of environmental
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group maintains close collaboration with medical physicists and oncologists at Skåne University Hospital, and methods developed by the group are used to analyse data collected within clinical studies
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imaging data. In this fully funded PhD project at DTU Compute, you will develop novel learning-based methods for X-ray nano-tomography. As state-of-the-art synchrotron imaging systems push towards
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design, beamforming, direction-of-arrival estimation, and software-defined radio systems . You will learn how to validate the sensing algorithms using a state-of-the-art motion capture system . You will
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. Responsibilities and qualifications The project will combine insights from quantum linear response theory, Krylov subspace methods, quantum phase estimation variants, and time domain correlation function
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beyond the study duration: extreme value theory for long term survival and cure chances”. This project will develop statistical methods and theory for analysing time-to-event data when a fraction of the
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methods, this in close interaction with the researchers developing the in vitro cultures and models. You support the design of new experiments through model-based analysis and simulation. Discover
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online learning methods deployed in converters/drives so that fleets of motor applications (e.g., pumps, fans, compressors) can self-quantify and aggregate flexibility for grid services with formal
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Robotics - Safe Autonomy in Shared Industrial Environments We are seeking an excellent candidate at the doctoral researcher level to develop perception, prediction, and planning methods that enable
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(ML) models. The doctoral researcher will also use state-of-the-art methods to make the ML models explainable, namely Deep Linear Probes and Latent Space Cartography. This work will be associated