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(preferably in Python, Matlab, R, or similar) We offer Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension
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assessment criteria Experience with programming (e.g. Python, MATLAB, Fortran or similar), numerical modelling, remote sensing, large datasets, or fieldwork is considered meritorious. Employment process
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Assistant Director, Treasury Planning (Hybrid) - Financial Services - Treasury Planning & Operations
Qualifications: Exceptional Excel skills: financial modeling and forecasting, complex formulas, scenario analysis, automation and data management using VBA and Python. Five to seven years of relevant experience
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laboratory. Where to apply Website https://networks.imdea.org/job/phd-position-in-ai-enhanced-secure-6g-services/ Requirements Research FieldEngineering » Communication engineeringEducation LevelMaster Degree
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evaluation methodologies. Experience deploying machine learning models to edge devices or mobile platforms. Strong programming skills in Python and experience with machine learning development environments
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to teach a computer programming course targeted to Mechanical Engineering Technology which includes microcontroller programming (Circuit Python or Arduino) Related teaching experience Professional
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- Experiencia en desarrollo y programación de red con lenguajes de alto nivel tales como Python, JavaScrit/Note, PHP. - Experiencia en bases de datos relaciónales como MySQL y no relacionales como MongoDB. Se
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.) as well as the basics of spectroscopy is desirable. Programming skills (Python) and experience or a strong interest in machine learning and data analysis are also expected, given the post-processing
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applications (https://www.cbr.washington.edu/analysis) to perform statistical analyses relevant to fish, dam, water, and natural resource management. The Software Engineer will play a lead role in the
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, Stata, Python, R). Conduct cross-city comparative research Map and analyse the geographical distribution of eviction patterns within and across cities; Examine similarities and differences in urban