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of thousands of molecules in our fully automated high biosafety screening facility CAPS-IT against multiple viruses. You will be responsible for the development and deployment of advanced machine learning models
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package contains: We are seeking a highly motivated postdoctoral researcher to work on reinforcement learning methods for public health decision-making in the context of epidemic emergencies, with potential
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; For this function, our Brussels Humanities, Sciences & Engineering Campus (Elsene) will serve as your home base. 3 - Profile What do we expect from you? You hold a PhD in machine learning, artificial intelligence
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students. YOUR TASKS Our research at BogaertsLab focuses on the cognitive science of learning and language. This position is part of the FWO-funded project “Growing a Statistical Mind: The Interplay Between
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for using AI to develop social engineering attempts. This project combines human subject research of learning and decision making, Human-Computer Interaction, and the advancement in AI methods
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strategies within it. You will combine archaeological and landscape data (maps, satellite imagery, archaeological datasets) with machine learning approaches to build a system that highlights promising
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machine learning approaches to build a system that highlights promising locations for archaeological research. You are also expected to play an active role in project coordination and in writing follow-up
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well as biologists. This in turn requires complete honesty and ease in revealing which fields the candidate is not an expert in, such that other team members can teach and support them Desirable: Having taken courses
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addresses themes such as sustainability transitions, environmental governance in social ecological systems, human-nature relations, citizen science, biodiversity and biosphere integrity, social learning
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addresses sustainability transitions, environmental governance, citizen science, ecological justice, social learning, climate adaptation and relationships between science, policy and society. We value