14 python-"DIFFER"-"NTNU---Norwegian-University-of-Science-and-Technology" positions at Monash University
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, with a focus on biodiversity conservation. You’ll contribute to high-impact publications and collaborate across disciplines to deliver research that makes a real-world difference. In addition a
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to molecular data. Strong knowledge of quantum, medicinal chemistry principles and chemical representations; familiarity with physics-informed ML and drug discovery is necessary. Proficiency in Python and deep
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Software Developer (Python/Django) Job No.: 678879 Location: The Alfred Centre Employment Type: Full-time Duration: 12-month fixed-term appointment Remuneration: $106,789 - $117,128 pa HEW 07 plus
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working with refugee and asylum seeker populations. Strong skills in statistical analysis, manuscript preparation and the use of software such as SPSS, Stata, R or Python are also essential. This is a rare
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atmosphere models Strong background in mathematics, physics, engineering or related field Experience in scientific computing, including C/C++, fortran, python, or MATLAB Version control and package management
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presentations. Clinical experience in the treatment of eating disorders (including BN and BED), across different service settings and age groups, using diverse treatment modalities. Proven ability to build and
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proficiency using analytical software such as R or Python, you are equipped to make a significant positive impact within our research team! About Monash University At Monash , work feels different. There’s a
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publications. It involves conducting systematic reviews and working with analytical software such as R or Python, with a focus on both independent and collaborative research. The role also requires experience in
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experience with analytical software like Stata, R, or Python, are essential. The ideal candidate will also have experience with geospatial tools. Additionally, you will have experience designing and managing
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from mobile devices and classify them into different categories or types of ringtones. The activities of the project include gathering a diverse dataset of audio samples representing various types