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Field
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Maxwell’s equations and scientific programming (e.g., Matlab, Python, C++) Competent in teamwork and presenting results in informative visuals Interpersonal skill: Ability to work under pressure, Ability to
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desirable. Proficient in Python, R, and ML libraries such as PyTorch or TensorFlow. Strong communication and collaboration skills; ability to work independently and as part of a team. Willingness to respect
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modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in or experience in environmental exposure
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, or a related field. Strong experience in statistical modelling, machine learning/deep learning, genomics and multimodal biological, and biobank data analysis. Proficiency in R, Python, Perl, and Linux
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, sufficient programming fluency (e.g., Python; familiarity with common ML tooling) to run computational experiments, and excellent communication skills, including writing for publication and presenting results
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modelling infectious disease dynamics, population dynamics or fisheries. Proven experience and ability programming in R or Python. Proven experience and interest in the application of mathematical modelling
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Center for Devices and Radiological Health (CDRH) | Silver Spring, Maryland | United States | 2 days ago
., Python, g-code) Data analysis Statistical analyses How to create reports Mentor: The mentor for this opportunity is Prasanna Hariharan (Prasanna.Hariharan@fda.hhs.gov ). If you have questions about the
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(preferably in R and/or Python). b) Preferential factors: Familiarity with spatial data analysis and/or Machine Learning methods will be valued. Workplan and objectives to be achieved: The work plan aims
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in research methods or data analysis Proficiency with data analytic programs (e.g., Stata, SPSS, AMOS, SAS, R/Python, etc.) Experience translating and disseminating research findings to broader
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-temperature conditions. Proficiency with data analysis tools and scientific programming languages (e.g., Python, MATLAB, LabVIEW). Commitment to safe laboratory practices and familiarity with experimental risk management