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human-animal-computer interaction lens, examining how digital tools shape farmer-cow relationships, perceptions of care, and welfare‑related decisions. The project will investigate how farmers engage with
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, Infected macrophage populations. Perform parameter estimation using optimization and machine learning approaches Develop numerical schemes for high-dimensional structured PDEs (pseudospectral methods
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 25 days ago
algorithms to estimate human shape and motion in images, videos and RGB-D sequences. Our approaches define the current state of the art, and we are constantly pushing these methods and systems in order to
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or replace established methods from computational engineering and computer simulation (such as the finite element method and constitutive materials models) to represent and exploit relationships along
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into its latest Ryzen processors, unlocking new possibilities for on-device AI acceleration. This project aims to maximise the potential of AMD’s cutting-edge hardware for healthcare computer vision
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role Conduct research on data quality and long-term reliability in smart sensor systems for industrial monitoring Develop methods, models, and computational tools for sensor data validation, anomaly
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-linear optimization techniques, projective geometry, as well as multi-view geometry, enabling you to develop and analyse methods for camera calibration, sensor registration, pose estimation, and 3D
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selection. However, currently, no unbiased method exists to accurately estimate genetic variance in populations under selection. The GEN project aims to develop and validate a general method to quantify
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tissues or reveal micro- or nano-structural features, like the small air sacs in lungs. To overcome these limitations, alternative X-ray imaging methods have been developed: X-ray phase-contrast and dark
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methods that can accurately model such processes remains an open and active research frontier. This PhD project is fundamentally about advancing that frontier, contributing new methods for generative