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Field
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, aiming at improving the information extraction and the of icy planetary bodies subsurface by radar sounder data processing. The selected candidate will be expected to develop novel machine learning methods
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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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information gain while minimizing testing hours to ensure these new technologies are reliable, sustainable, and affordable. Key Responsibilities Research & Development: Develop algorithms to estimate survival
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application! Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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complex, three-dimensional microstructure, and understanding how that microstructure influences electrochemical performance requires methods that can bridge the scales from 3D imaging to functional
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well as developing methods to study and characterize these processes. Within the research group, we highly value a positive work environment characterized by respect and care in our relationships with one another. We
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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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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 17 days 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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systematically improve the quality of production processes and final products. Continuous improvement must be implemented as a managed and ongoing system supported by modern quality management methods and computer