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experience. Strong coding skills in commonly used scientific languages (e.g. Python, Matlab, shell script, C) Demonstrated experience in performing simulations at the atomic-scale, including density functional
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proficiency in data analysis tools (e.g., Python, R, SPSS). Proven track record of conducting research in AI safety, governance, or related areas, with publications in peer-reviewed journals or policy reports
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and computational methods using R or Python, while continuously enhancing technical proficiency through structured training. Develop, manage, and quality-check complex datasets from diverse sources
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analysis of large datasets using Python, Matlab, or other programming languages - Experience with embedded system, particularly IoT sensor development. - Experience with optical sensor development preferred
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modelling physics of water flow map data will be considered an advantage when candidates are ranked. Experience with scientific programming using Python, MATLAB, C++, Julia, or similar is a requirement
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research outputs Data science skills, especially data analysis and prediction modelling Proven ability to write code in Python Experience working in a research team Excellent writing and communication skills
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programming languages relevant to computational modeling (e.g., Python, R, or similar). Data Analysis Tools: Experience with statistical software and data visualization tools (e.g., SPSS, Stata, Tableau). AI
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methods • Comfortable in mathematical modeling and analysis, including writing proofs • Proficiency in scripting in and performing data analysis in Python or Matlab • Research independence More
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formats. Experience with AI and deep learning algorithm development for medical image analysis. Familiarity with SQL, Python, Tensorflow, Scikit-Learn, and Pandas. Additional Qualifications Considered
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technologies, is highly desirable. Skills: Strong knowledge of clinical informatics frameworks, standards, and methodologies. Proficiency in data analysis software (e.g., R, Python, SAS, SPSS, SQL) and