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discipline. Strong programming skills in C, C++, and Python. Experience with software design, development, debugging, testing, and maintenance in Linux-based environments. Experience using version control
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evaluate solutions given problem statements in key generation and relaying across multiple hops in quantum key distribution (QKD) networks. Demonstrate functionality of solutions. Document and publish the
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multi-institutional partners to ensure protocol fidelity and reproducibility across sites Develop and maintain scalable, reproducible data pipelines using Python/MATLAB and relevant neuroinformatics tools
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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Synapse, Azure Data Factory, and Microsoft Fabric, along with an understanding of Spark, is desired. Experience with tools such as with Python, C#, Powershell, Power BI, SAS, Stata, and Web technologies
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for education requirement. Preferred: Proficiency with R and at least one additional coding language (e.g., Linux, Python) Comfort with data management, quality control, and standard practices Proficiency with
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detection is being modeled, thereby allowing the detection rate to depend on the time of day. The postdoctoral researcher will have access to large, pre-existing datasets covering multiple sectors
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datasets from multiple sources into a unified and coherent data framework. Data curation, cleaning and harmonization, including taxonomic standardization and alignment with existing reference databases. Data
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using integrated measurement, modelling, and statistical approaches. The team works across multiple spatial scales to understand how environmental exposures affect human health and to generate scientific
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collating and managing data with version-controlled programmatic workflows in R and/or Python, including large volumes of high-frequency sensor data and model outputs; working with investigators to design and