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assimilation on weather prediction Perform data-preprocessing, quality control, error modelling and correction Write reports and scientific publications Job Requirements: PhD qualification degree in Atmospheric
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into advanced manufacturing processes. The overall objective is to develop a reliable and predictive digital twin dedicated to polymer processing technologies, particularly injection moulding, by combining
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command of English. The candidate must possess a strong publication record that demonstrate their capacity of using bioinformatic platforms in life science research. The candidate should be proficient in
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candidate (m/f/d) for the “Development of a digi-tal twin and model predictive control for filtration processes”. Project Join a research initiative in the field of Industry 4.0 and cyber-physical systems
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systems and develop predictive tools for mechanical failure. Our team is highly interdisciplinary and international, bringing together researchers with backgrounds in materials science, mechanics, and
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Prof./Associate Prof./Assistant Prof. in AI/Robotics for Aircraft Maintenance / Low-Altitude Economy
, is first in Hong Kong for four subjects, and is in the global top 100 for 24 subjects. For further details about the University, please visit PolyU’s website at https://www.polyu.edu.hk/ . In line
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, physics of fluids, flow control... The main objective is to develop numerical tools to efficiently predict and to deeply understand flows in more and more physically and geometrically complex configurations
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Albert-Ludwigs Universität Freiburg | Freiburg im Breisgau, Baden W rttemberg | Germany | 19 days ago
2026 Where to apply Website https://uni-freiburg.de/stellenangebot/00005130/ Requirements Research FieldEngineering » Mechanical engineeringEducation LevelMaster Degree or equivalent Skills
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components for HVAC controls, including Robertshaw, Delta, and Delta V systems Contributing to the long-term goal of reliability-centered maintenance by assisting in preventative and predictive maintenance
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to estimate and predict the parameters of interest characterizing the agri-food matrices. Where to apply Website https://pica.cineca.it/ Requirements Research FieldAgricultural sciences » OtherEducation