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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
the development of agentic artificial intelligence systems. Unlike conventional conversational systems, AI agents can generate action plans, invoke external software tools and APIs, communicate with other agents
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data analysis Strong foundation in mathematics Strong programming skills in Python (Python Data Stack, PyTorch, etc.). Good oral and written presentation skills in Norwegian/Scandinavian language
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parte de los créditos correspondientes), así como la experiencia demostrable en algunas de las siguientes áreas: Sistemas U-Space, lenguajes de programación (TypeScript,JavaScript,Python), y simulación
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effects between regions with different policies; Identifying tipping points at which climate and transition risks cause the financial sector to shift from a facilitating to a constraining role in spatial
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) solutions, multimodal signal processing, and digital biomarkers for accessible sleep monitoring in adult and pediatric populations with different health conditions. The aim of the project is to develop new
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programming (Matlab and/or Python); Hands on with laboratory work, skilled in experimental design; Creativity, assertive attitude, and perseverance The selection process will start immediately; the intended
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. As a PhD candidate, your goal is to develop new methods for assessing climate risk due to consecutive droughts and at different scales in Europe. Based on these risk assessments, the PhD will develop
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concurrently exploring how age- and sex-related differences in key muscle qualities and force–velocity–power characteristics influence functional capacity, performance, and quality of life. Mechanistic profiling
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, structure preserving deep learning, stochastic differential equations, generative AI, numerical optimization. Strong programming skills (Python, Julia, Jax). Experience with numerical optimization is also
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design for different examples (e.g. subsidies for multi-species cropping, mixed-provenance restoration, or age-structured fishery management). The goal is to identify barriers, leverage points, and