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-based and farm models with a focus on biogeochemical and hydrogeological fluxes. Knowledge of greenhouse gas inventories (methane, ammonia, nitrous oxide) Proficient skills with scripting (R, Python) and
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and data analysis skills (e.g., Python, R) Solid understanding of machine learning, deep learning, and data modeling techniques. Preferred Qualifications: Prior working experience with EHR data, machine
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analysis of genomics data, including in R or Python. Strong project management skills Ability to develop, manage and maintain internal and external working relationships Highly developed written and verbal
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. Applicants should demonstrate expertise in programming languages such as Python and/or R, as well as experience working with high-performance computing clusters. The successful candidate will be a team player
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-scale data analysis you will be able to demonstrate your expertise in using R and Python to process and analyse genomic data and to employ learning frameworks. Appointment is at either a grade 4 or grade
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. Use of radiation transport codes, especially MCNP, Serpent, OpenMC, or an equivalent code. Experience with uncertainty quantification methods. Experience with computer programming (Python, C
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) is an advantage Experience in software tools such as Origin, Matlab, Python/Matplotlib or similar programs for data processing and evaluation. Knowledge of a relevant programming language complements
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publication record in reputable peer-reviewed journals is highly desirable. Proficiency in programming, particularly in R, Python, or other relevant languages, is required. Qualified candidates should also meet
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for plants and Physics. A background in plant ecophysiology would be ideal, but is not required. · You have programming experience, knowledge of Python and Git is a plus. · You have a
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industrial experts. Nice to have: Proficiency in programming languages (Python, MATLAB, or similar software) for data analysis/model automation. Prior industrial collaboration or scale-up project experience