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reactions, catalyst surfaces and interfaces, reaction mechanisms, activity and selectivity develop reproducible atomistic simulation and high-throughput workflows using Python, ASE and relevant DFT software
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. Python programming, or a willingness to learn. Higher degree student supervision. Strong initiative, resourcefulness and the ability to work effectively to deadlines. About UQ As part of the UQ community
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learning or a related field experience in the development of machine learning models using Python and pytorch expertise in two or more of the following technical areas: implementation of signal processing
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in the development of machine learning models using Python and pytorch expertise in two or more of the following technical areas: implementation of signal processing systems, data collection
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expertise developing, validating and deploying advanced statistical and machine learning models using Python, R, or similar programming languages in a research environment. Experience working with melanoma
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) statistics and data science Experience with mathematical modelling (e.g., linear algebra, linear models methodologies) Demonstrated programming skills in C/C++, Python, R or comparable languages. Experience
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or equivalent approaches. Automated experimental testing, instrument control or data acquisition using tools such as LabVIEW, Python or MATLAB. Pre-employment checks and declarations Your employment is
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arising from finite fields, projective and polar spaces, and related structures. Apply computational methods (e.g. Magma, GAP, SageMath, Python) to test conjectures and explore new mathematical directions
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or equivalent approaches. Automated experimental testing, instrument control or data acquisition using tools such as LabVIEW, Python or MATLAB. Pre-employment checks and declarations Your employment is
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using tools such as LabVIEW, Python or MATLAB. Pre-employment checks and declarations Your employment is conditional upon the successful completion of all pre-employment or background checks required