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Practical experience with vector network analyzers and on‑PCB LRM/TRL calibration/de‑embedding. Proven experience in behavioural modelling and DPD (MATLAB/Python) Desirable Criteria Knowledge, Skills
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 20 days ago
API development (Python or C# is an advantage), · practical knowledge of relational databases, SQL and ORM frameworks, · version control (Git) and software artifacts handling in containerised
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platforms (e.g., Azure, AWS, Databricks) and version-controlled collaborative development environments (e.g., GitHub). • Strong programming proficiency in Python; experience with ML frameworks such as PyTorch
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and academic excellence. Ready to be part of our team? Let’s shape the future together! Where to apply Website https://iventajobdata.eu/bestmedia/img/2293325/1915754/cl/7c7695ab265bad0de8c30
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good academic & judicial standing with the University of Arkansas Have programming experience in Python and/or R Must have previously completed Calculus I and/or Calculus II or equivalent Preferred
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Learning for Cybersecurity, AI for 3D Imaging, Recommender Systems, Quantum AI, Blockchain AI, AI for Autonomous Systems Foundational courses (for Connect pathway students): Python programming, Mathematical
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but not limited to Stata and R. Produce summary statistics and conduct basic statistical analyses Writing scripts in python to automate processes and for webscraping Assist with data analysis and
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or more programming languages or statistical packages (e.g. Python, R, SPSS, SAS, etc.) Familiarity with data sources such as ICPSR, Mergent, Roper, Social Explorer, World Development Indicators,Â
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optimization of nonlinear problems will be essential. The researcher must also be familiar with image manipulation and software development in Matlab or Python. The ability to collaborate both in academia and
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Demonstrated experience in statistical analysis of biomedical or clinical datasets Strong programming skills in R and/or Python Experience in data cleaning, management, and integration from multiple sources