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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 8 days ago
numerical results with available observational and experimental evidence in geophysical and astrophysical contexts. Your qualification PhD in fluid dynamics, physics, applied mathematics, geophysics
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27.03.2026, Academic staff The research group Cyber-Physical Systems of Prof. Matthias Althoff at the Technical University of Munich offers a PhD/Postdoc position in the area of safe data-driven
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kinetic models and their hydrodynamic limits. Dispersive phenomena in kinetic theory. Quantum gases. Applicants must hold a PhD degree in mathematics, physics or a related field. We seek candidates with
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–based, web-enabled decision-support tool for farmers, using machine learning (random forest) predictive models. Working closely with the PhD student and PIs to ensure rigorous model development
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to reanalysis and model data. Explore and contribute new research ideas. Present results at conferences and meetings. Write manuscripts and publish papers in scientific journals. Supervise master’s and/or PhD
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uncertainty associated with high renewable penetration in a more systematic and effective way. Specific responsibilities may include: • Developing models (mathematical + software) of existing grid
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. Contribute to development of research proposals and new research initiatives. Required Qualifications – Experience, Education, Knowledge & Skills PhD in Physics Education Research, Physics, Mathematics
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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria PhD in computer science, deep learning, or data science. Experience with multimodal models for biological data. Website
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2 Apr 2026 Job Information Organisation/Company THE UNIVERSITY OF HONG KONG Research Field Computer science Mathematics Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1
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methods and research software empower modern biomedical research. Your mission As a Postdoc you will help build the next generation of multimodal and explainable AI models for personalized risk prediction