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Field
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/ Computer Science, Mechatronics / Mechanical or Electrical Engineering, or related fields in Engineering, Computer Engineering or Applied Mathematics Programming Skills: Programming Experience with Python, C/C++, ROS
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of the candidate Essential requirements: A 1st class or 2.1 degree (or equivalent) in Environmental Science, Remote Sensing, Computer Science, Surveying Engineering, or related field Strong coding skills (Python
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the simulation models using appropriate tools (e.g., AnyLogic, Simio, Siemens Plant Sim, Python, MATLAB or other relevant simulation platforms) Evaluate and validate the proposed framework and assess its impact on
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, or other related academic discipline. Good programming skills (preferably Python). Background/work experience in Cyber Security, Machine Learning, and Finance would be highly beneficial. How to apply
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with statistics or programming in R/python/MATLAB desirable. Mode of study Full-time Start date 1 October 2026 Additional Funding Information This project is fully funded for 3 years. Funding includes
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, or the application of machine learning to registry data is highly valued. Experience in statistical analysis, including the use of statistical software such as STATA, R, Python, or SAS, will be viewed positively
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modeling with SUMO. Programming transport modes with Python. Integration of climate constraints into a transport model. Emergency and disruption management. Where to apply Website https://sede.uvigo.gal
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robots for facade operations. Programming in MatLAB and Python. Navigation in GNSS-denied environments. Publicacion of scientific papers. Development of project deliverables. Where to apply Website https
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proficiency in Python. Knowledge in Statistical physics and Network science, and interest in complex networks and interdisciplinary research are a plus. The position is for 3 years, and will be located
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validation on simulated and real data Skills Abstraction capabilities, strong programming skills in C/C++ and Python, collaboration skills. English is needed. REFERENCES [0] C. Bekker, S. Rothmann, M. Kloppers