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to the technical lead of Cardiac AI. The successful candidate will have demonstrated experience in and be responsible for: Develop and oversee the development and maintenance of Python scripts to merge data extracts
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using both R and Python Develop and conduct complex statistical analysis plans for research studies, including the application of statistical analysis techniques such as regression, text mining, topic
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Australian National University | Canberra, Australian Capital Territory | Australia | about 6 hours ago
. The candidate will have a passion for developing innovative instrumentation and analytical methods to enhance accelerator performance and safety. Experience with programming languages such as C++ or Python, and
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tool Support coding tasks across various research projects using Python, JavaScript, and other relevant programming languages Maintain and develop digital tools such as pythermalcomfort and create new
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countermeasures. The successful applicant will work closely with collaborators and co-investigators across multiple schools within SET on theoretical and algorithm development and implementation, assist
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to the development and maintenance of science data processing pipeline solutions. This role suits an expert Python programmer with experience in scientific workflows and high-performance computing (HPC), who thrives
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leadership and mentorship to multiple teams. To be successful in this position, you’ll have experience in: Architectural Leadership: Define and drive the technical architecture and evolution of Azure-based
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, administration and the integration of databases with software systems via APIs. Experience with developing data pipelines, using Python and Postgres, experience with DevOps and deploying software in Azure, with
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) in FPGA design, machine 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: design
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large and diverse organisation. Expertise in Power BI, and experience in using analytics programing languages, such as SQL, R or Python. Highly developed data analysis skills to query and validate data