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to deliver accounting and financial reporting, budgeting and forecasting, treasury and debt, internal controls and compliance, purchasing and procurement, accounts payable, payroll, and student accounts
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regularly in its various training and research activities, as well as the weekly seminars in IDAEA-CSIC. Where to apply Website https://www.idaea.csic.es/job-offer/phd-position-understanding-and-predicting-n
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, audience engagement, and sentiment shifts over time. Pattern Recognition & Predictive Analytics: Apply pattern recognition methodologies across multi-touch user journeys, enrollment/conversion funnels, and
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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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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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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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Albert-Ludwigs Universität Freiburg | Freiburg im Breisgau, Baden W rttemberg | Germany | 16 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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on the structural integrity of metallic materials for hydrogen energy applications, with a focus on predicting their service life and failure mechanisms. The research will be carried out in close collaboration with