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, Economics, Business Analytics, Data Analytics, Energy Finance, Accounting, or a related field is desirable. Experience with empirical research methods and programming languages such as Python, R, Stata
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characterisation techniques or laser systems Background in semiconductor device fabrication or cleanroom processing Experience with numerical simulations (e.g., FDTD, COMSOL, Lumerical) Programming skills (Python
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with Linux and scientific programming in R and/or Python. If your native language is not English and you do not hold a degree from an institution in which English is the language of instruction, you must
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Python and/or C++. Experience with scientific software development is an advantage. An interest in quantum algorithms and the motivation to contribute to one of the world’s emerging research areas. Strong
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following would be advantageous: Programming in Python, R or a comparable language. Using machine-learning frameworks such as PyTorch, TensorFlow or scikit-learn. Working with audio, video, behavioural
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following would be advantageous: Programming in Python or a comparable language. Using machine-learning frameworks such as PyTorch or TensorFlow. Working with image, video, time-series or sensor data
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collaboration with national and international stakeholders, the project aims to establish a validated, data-driven design framework. Key outcomes will include an open-source Python toolkit, measurable
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sensing, AI-based methods and data-driven hydrological models, as well as experience in operationalising real-time hydrological systems and programming in, for example, Python. In addition, you are expected
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implement Python scripts for the automated control of electron microscopes; design and execute automated experiments, including real-time feedback loops between acquisition and data analysis; maintain
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, and sustainability transitions; Interest in material flow analysis, life cycle assessment, environmental modelling, and scenario analysis; Experience with programming and/or data analysis (e.g. Python