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computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and interactive prototypes for scenario
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Solutions at the UM6P Data Center. Innovate and improve image analysis algorithms for plant trait quantification. Collaborate with international research teams and contribute to joint publications and
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characterization, distribution, diversity, and transmission mechanisms between rhizobia and hostel plants. Main responsibilities: The selected candidate will be expected to: Conduct research as part of the project
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Postdoc Impact of Computational Infrastructures on Public Institutions and Administration of Justice
of “clouds”. Popular discussions revolve around the topics of data protection, algorithmic regulation, and asymmetric ‘technological dependencies’ that raise concerns around monopolies and “digital sovereignty
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for Basic Research in Program Verification (CPV) include: extensions of higher-order concurrent separation logics (such as our Iris logic, see iris-project.org ), e.g., to reason about distributed systems
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control and energy management strategies, including centralized / distributed control approaches, for ESS coordination and ancillary service delivery. Develop optimization algorithms and Al-based methods
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predictive modelling Development of model predictive control algorithms for energy-efficient and flexible building Contribution to prescriptive maintenance strategies and user-centric digital interfaces
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both academic research and industrial applications. In addition to theoretical research, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation
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experimentally verified results is a necessary: - Autonomy with collaborative intelligence - Distributed task and motion planning - Predictive collaboration with heterogeneous teaming - Multi-agent navigation in
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algorithms, NLP models, and LLMs to analyze complex data. Designs and implements novel data science methodologies for predictive modeling, causal inference, and probabilistic analysis in clinical and