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education, research, or knowledge-intensive industry. The position reports to the Unit Leader of Colorlab. About the project The research will address the growing need for reliable methods that can assess the
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focus on combining simulations using spatial-genetic-demographic individual based models (e.g., using the software SLiM), machine learning approaches, and genomic data to estimate larval dispersal
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: Design, implement and characterize innovative sensing systems based on different sensing principles such as ultrasonic, optical and chemical sensors. Investigate sensor behavior under varying environmental
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in-house design. Strong ability to use simulation software tools including finite difference time domain methods (FDTD), eigenmode expansion methods (EME), or finite-element methods (FEM), using tools
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, integrate genomics, epitranscriptomics and transcriptomics data, and contribute to the development of novel systems biology and bioinformatics methods for RNA therapeutic target discovery. The project is led
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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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deviation from the healthy distribution. But in the absence of labels, how should we direct the model to learn relevant features, and how can we determine which features are relevant? These questions
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Technology » Computer technology Technology » Communication technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 4 Oct 2026 - 23:59 (Europe/Oslo) Country
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. The PhD will contribute directly to the development of technologies that may accelerate drug discovery, personalized medicine, and the transition toward advanced animal-free testing methods. Your immediate
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and structure of healthy anatomy and detect any deviation from the healthy distribution. But in the absence of labels, how should we direct the model to learn relevant features, and how can we determine