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Field
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modelling and statistical computing programs and languages such as Python and R Please refer to the Position Descriptions for other duties, skills and experience required for this position. Welcome
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. Candidates must also have excellent programming skills in a relevant scientific language, such as Mathematica or Python, to facilitate advanced data analysis of measurement outputs. Apart from being able
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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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such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological
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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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processing would be an advantage. Proficiency in statistical software (e.g., R, Python, SAS, or Stata). Experience with clinical informatics approaches (e.g., cluster analysis, machine learning, Bayesian
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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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constructive feedback, and strong organizational skills Passionate and clear about your own research interests Adept in running statistical analyses (e.g., Stata, R, SAS, MPlus) and/or in coding (e.g., Python
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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
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) to genome-scale datasets · Extensive programming experience in R and/or Python (ideally both) · Strong writing, communication, and interpersonal skills, including a proven ability to work both independently