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contributions in relevant fields. Proficiency in programming languages such as Python and MATLAB. Experience with system modeling tools such as TRNSYS, Modelica, or equivalent platforms. Strong analytical
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technologies like Azure Data Explorer (ADX), PostgreSQL, MongoDB, and data driven machine learning tools such as Spark, Power BI. Experience with optimisation, simulation and data analysis tools such as Matlab
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, XPS/AFM, electrical probing; DoE/statistics (Python/Matlab a plus). Strong documentation, safety discipline, and clear communication in English. Process integration & optimization; root-cause/failure
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); familiarity with phase-noise / linewidth / RIN measurement and coherent detection is a strong advantage Competent in scripting and data analysis in Python or MATLAB, with comfort using version control (Git) and
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, efficiency, and timing trade-offs in low-light imaging. Applicants should have competence in data acquisition/analysis and scripting for instrument control (e.g., Python/Matlab/LabVIEW) Applicants preferably
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) would be an added advantage Possess good programming, optical instrumentation, automation and data processing skills (e.g. C++, LabVIEW, Zemax, OSLO, TracePro, MATLAB, Python, ImageJ) Proven publication
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publication records will be preferred. Experience in matlab, MEEP, RCWA and other softwares and algorithms. Excellent publication track records. Good understanding of nonlinear and quantum optics. Strong
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measurements, awareness of noise, efficiency, and timing trade-offs in low-light imaging. Applicants should have competence in data acquisition/analysis and scripting for instrument control (e.g., Python/Matlab
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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning