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studies. Develop and apply advanced statistical methods and machine learning techniques using tools such as R and Python. Integrate and run process-based models (e.g., crop models, hydrologic models
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, and SageMaker. Your expertise in data transformation languages such as SQL and Python will be essential in ensuring data quality, integrity, and adherence to established data governance standards. We
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(Excel or Power BI) and in at least one data science tool (Python or R) and have prior experience working with other stakeholders to deliver successful learning outcomes. Experience in performance
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such as Python, Perl, Java Script, and shell scripts. Collaborate with team members on the design, implementation, and support of standardized automation systems. Lead a group of team members on design
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to provide visa sponsorship for this position. Basic Qualifications: Proficiency in coding (Python) and deep learning frameworks (PyTorch) with a drive to enhance these skills. Familiarity with one of the AI
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or solar-planetary science, with demonstrable expertise in imaging or spectroscopy of auroral emissions. Strong programming skills (e.g., Python or C++) and experience with space-based data analysis
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. Experience with next-generation sequencing and/or exome/whole genome sequence analysis. Computer programming (e.g. R/Python) and bioinformatics experience. Familiarity with NGS clinical testing, databases
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metamaterial design is a plus. Proficiency in programming (e.g., MATLAB, Python, or C++) and relevant simulation software (COMSOL and/or Abaqus). Excellent communication skills and a proven record of
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conducting and reporting epidemiological studies using real-world data is essential. Proficiency in using statistical software packages such as R, Stata, SAS, or Python is also required. Strong organisational
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, AWS Glue, Talend, etc.). Proficiency in SQL, Python, and/or other programming languages commonly used in data engineering as well as data transformation tools (e.g. DBT). Solid understanding of database