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modeling Structural dynamics analysis Rules and design guidelines for structural engineering Blast, impact or shock loading Programming and scientific computing (e.g., Python, Matlab, C++ or similar
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of system and data confidentiality and complete any other requirements. Desirable skills: Experience in programming (C, python, or similar). Knowledge in machine learning or distributed systems. How to apply
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candidates will have: A solid grounding in mathematical or physical sciences Interest in dynamical systems and complex system behaviour Some coding experience (Python and/or Julia) Enthusiasm for working
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algorithm development Proficiency in at least one programming language, e.g, Python, Julia, C++, or similar Interest in applications in transport, logistics, or operations planning Applicants in the final
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for Bayesian/statistical modelling with uncertainty analysis or programming skills in Python, MATLAB or equivalent and a background in hydraulic, kinetic or systems models. Also highly desirable to have
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significant programming experience ideally in C, C++, R and/or Python. You must have good written and oral communication skills in English. PLEASE NOTE: For detailed information about what the application must
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data with computational modeling Programming skills in Python, R, or another relevant language. Interest in machine learning, statistical modeling, structural bioinformatics, or analysis of large-scale
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frameworks. Further, it would be advantageous for applicants to demonstrate proficiency in at least one scientific programming environment such as Python, MATLAB, or R. A good understanding of hydrodynamic
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Intelligence/Machine Learning (AI/ML) methods in agriculture (Agro-AI/ML); and Experience in programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic
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(see below) are also encouraged to apply. Proficient in at least one programming language, preferably Python or R. Experience in any of the following areas: large scale sequence analysis, microbial