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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
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statistical software including Stata, R or SAS, python. Have an emerging publication track record with high impact publication(s) within biostatistics, cancer and health services research or another related
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deep learning and large language models, is desirable. Experience with Python and common machine learning frameworks (such as PyTorch or TensorFlow) is highly valued. Familiarity with topics such as
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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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gases and atmospheric chemistry, climate and/or air quality Strong capability in analyzing and interpreting complex datasets, including proficiency in Python, R or similar programming tools Demonstrated
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reconstructions, thermomechanical modelling, palaeoclimate modelling and/or landscape evolution modelling strong scientific programming capability in Python, C/C++ or similar programming languages a proven record
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scientific programming using Python or similar languages, or the demonstrated ability to rapidly develop coding capability a strong publication record relative to career stage in relevant research fields
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Familiarity with Python and Callista data is desirable About Monash University At Monash , work feels different. There’s a sense of belonging, from contributing to something ground breaking – a place where
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such as SPSS, R or Python; Power BI or equivalent a strong advantage. Demonstrated experience designing and validating quantitative analyses and models, with a focus on rigour, accuracy and reproducibility
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coordination Data models, mapping, databases and integrated systems Written communication and documentation Attention to detail Stakeholder engagement SQL, Python, Power BI or other reporting tools