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R and Python and AI software and a willingness to adopt new technologies will also support your success. If you're passionate about research that informs better science and you're ready to contribute
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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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levels in sleeping infants. The successful applicant will develop significant skills in fNIRS data collection, data mining techniques and data modelling (Python/Maltab). Lab head Professor Colette McKay
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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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discipline. Expertise and experience in computer programming, especially in Python. A strong work ethic, and the ability to work well independently, and as a member of a broader team. Be an Australian citizen
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, analytics, or software development. Proficiency in scripting and programming languages (e.g. SQL, Python), and experience in developing data solutions across desktop and web platforms. Practical experience
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of bioinformatics (RNA-seq pipelines, Python/R) and sequencing technologies (nanopore, single-cell, ATAC/ChIP-seq). Knowledge of genetic regulation and lncRNA function in immune contexts Excellent data analysis and
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. Desirable Experience with electromagnetic FDTD and mode-solving simulation tools (e.g. Lumerical, Tidy3D) and Python-based mask layout tools (e.g. GDSFactory, IPKISS). Hands-on experience in integrated
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in Python programming and Linux environment. An emerging profile in research in the discipline area. Evidence of publications in reputed refereed journals and presenting at conferences. Evidence of
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. This role demands deep expertise in Databricks and Microsoft Azure. Proficient in data modelling, integration, and design, with hands-on expertise in SQL, Python/PySpark, Unity Catalog, and database schema