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technologies. LIST bridges scientific excellence and applied research to design solutions that address real-world challenges and create positive impact. The quality of weather forecasts, seasonal simulations
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QGG - Aarhus University seeks a postdoc researcher in sustainable breeding: developing simulation...
for Quantitative Genetics and Genomics (QGG) holds a prominent position in research in developing breeding plans and breeding goals for sustainable production. We are developing simulation tools for breeding
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radio access and/or core network standards, implement the features in MATLAB and/or OpenAirInterface software for computer simulations, and conduct theoretical research to submit proposals to the ongoing
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, and tracking), the creation of explainable AI methods to interrogate scientific datasets, and the design and implementation of mechanistic models of biological processes that work together
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ICT Services & Applications. Your role Conducting independent research on advanced communication systems in optical wireless communications Developing system-level models, simulations, and performance
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of oxygen and Earth’s first global glaciation about 2.4 billion years ago. Key responsibilities: design, run, and analyse equilibrium and transient simulations with a coupled Earth-system model
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infrastructure, modern workspaces, and very well-equipped labs Contact details: For questions regarding eligibility or the application procedure, please contact: Dr. Ana Depetris Chauvin | fellows4fungi@leibniz
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to communicate effectively in English Research experience on process-based and ML models to simulate nutrient flows in agro-ecosystems Strong skills with scripting (R, Python) and programming Ability
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Internet, Earth Observation, and Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal
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, or biophysical simulations. Demonstrated interest in biological systems, prior experience in biological modeling and in transcriptomic data analysis. Proficiency in programming (e.g., Python, R) and familiarity