49 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" Postdoctoral research jobs in Australia
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experience experience in molecular biology or genetic engineering techniques ability to learn how to conduct protein purification and characterisation ability to operate and maintain biological equipment (e.g
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culture that encourages growth, innovation, and meaningful impact. About you You thrive in collaborative settings and are committed to fostering an inclusive and equitable learning and research environment
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the Position Description for this role. Applications Close Monday 19 January 2026 11:59 PM Where to apply Website https://www.timeshighereducation.com/unijobs/listing/405304/postdoctoral-resear… Requirements
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, measure transport and machine learning on developing a novel mathematical framework for identifying reduced dynamical models of high-dimensional complex multi-scale systems. The project will develop fast
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related discipline): Computer Science, Artificial Intelligence, or Machine Learning Economics or Econometrics (particularly applied micro, behavioural, or decision-focused modelling) Applied Mathematics
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density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data, including with the use of machine learning use this knowledge to design
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machine-learning based approaches for extremely precise radial velocity studies and exoplanet spectroscopy with the NEID, HPF, and MARVEL facilities, and pursue related exoplanet and stellar science. We
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collection and management for research, as well as basic knowledge of both quantitative and qualitative data analysis principles. Demonstrate high levels of computer literacy, including proficiency in learning
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collection and management for research, as well as basic knowledge of both quantitative and qualitative data analysis principles. Demonstrate high levels of computer literacy, including proficiency in learning
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an equivalent discipline) expertise in statistical and machine learning approaches, with the ability to apply advanced methods to complex environmental and agricultural datasets proficiency in R and/or