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Field
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. Desirable Criteria Experience implementing machine learning or deep learning models (e.g., neural networks, probabilistic learning methods). Knowledge of state estimation techniques, such as Kalman filters
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Course: PhD studentship Project title: Exploring a One Welfare approach to human-animal-computer interaction in digital dairy technologies Principal supervisor: Charlotte Doidge Other supervisors
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 1 day ago
to identify the object landmarks that can be used for localization in a given environment. Moreover, object detectors used in these methods must be finetuned to recognize objects beyond common categories
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through a One Welfare and human-animal-computer interaction lens, examining how digital tools shape farmer-cow relationships, perceptions of care, and welfare‑related decisions. The project will investigate
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tasks to work with, enhance or replace established methods from computational engineering and computer simulation (such as the finite element method and constitutive materials models) to represent and
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minimise health risk. The aim for this project is to investigate the use of statistical AI methods for a) estimating the synergistic effect of temperature, humidity and air quality on human health (mortality
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 21 days ago
Tong Zhang. Communication-efficient distributed optimization using an approximate newton-type method. In International conference on machine learning, pages 1000–1008. PMLR, 2014. [6] Lucas Theis, Wenzhe
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physics or theoretical chemistry, with interest in electronic-structure theory and method development. Experience in computer simulations and programming is advantageous. Very good communication and writing
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candidate will be supervised by P.M. Congedo, E. Denimal Goy and Olivier Le Maître, experts in uncertainty quantification methods. The work will be conducted in the Platon team, a joint research group between
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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