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, such as Python and MATLAB (by MathWorks), for data analysis, simulation, and automation tasks. The successful candidate may be required to complete a number of pre-employment checks, including: right
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experience Proficiency in Python programming and experience with databases, SQL, and data modelling Demonstrated experience developing data pipelines and ETL processes using tools such as Apache Airflow
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. Desirable Experience with electromagnetic FDTD and mode-solving simulation tools (e.g. Lumerical, Tidy3D) and Python-based mask layout tools (e.g. GDSFactory, IPKISS). Hands-on experience in integrated
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, analytics, or software development. Proficiency in scripting and programming languages (e.g. SQL, Python), and experience in developing data solutions across desktop and web platforms. Practical experience
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in Python programming and Linux environment. An emerging profile in research in the discipline area. Evidence of publications in reputed refereed journals and presenting at conferences. Evidence of
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, random forests, etc.), and languages like R, Python, or Julia for health data analysis. Experience in backend/frontend development, data visualization, and web apps using JavaScript, Python, and Linux
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information systems. Proficiency in SQL, Python, or other programming languages used for data manipulation and ETL processes. Experience with cloud platforms, such as AWS or GCP, for data storage and processing
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to optimise research outcomes. Advanced Data Cleaning and Analysis: Clean,engineer, prototype, and deploy statistical and machine learning models using Python and/or R to solve complex problems; maintain and
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microcontroller platforms and FPGAs (with proficiency in HDL such as Verilog) development of hardware control software stacks (with proficiency in C++ and Python) at the level of the system software engineer