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Field
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skills in Matlab and/or Python are required. These should be documented, for example through a GitHub profile or similar. Familiarity with numerical methods for solving Maxwell’s equations, particularly in
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relevant programming languages (e.g., Python, MATLAB, R) is a requirement. Familiarity with downscaling and bias correction of climate data (e.g., from CMIP/PMIP) is an advantage. Experience with
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of machine learning techniques Proficiency using data science tools (e.g., Python, R, MATLAB, MySQL, Jupyter Notebooks) Excellent verbal and written communication skills including the ability to communicate
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processing, medical/biological applications, sensor technology and sensor data, Matlab framework. The applicant must be fluent in oral and written English. Advantageous prior experience: elderly care
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in scientific coding and data analysis programming languages, such as Python or MATLAB, is a requirement. Experience with running snowpack and/or Earth System Models is a requirement. Experience in
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signal processing Mandatory experience and formal training: signal processing, medical/biological applications, sensor technology and sensor data, Matlab framework. The applicant must be fluent in oral and
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or MATLAB, is a requirement. Experience with running snowpack and/or Earth System Models is a requirement. Experience in field instrumentation or other demonstration of observational data curation is an
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. Proficiency in relevant programming languages (e.g., Python, MATLAB, R) is a requirement. Familiarity with downscaling and bias correction of climate data (e.g., from CMIP/PMIP) is an advantage. Experience with
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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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atmosphere models Strong background in mathematics, physics, engineering or related field Experience in scientific computing, including C/C++, fortran, python, or MATLAB Version control and package management