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printed circuit board prototyping Basic data analysis using MATLAB or Python Experience with microcontrollers Problem solving skills and out of the box thinking A combination of education and relevant
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make a difference in the world! Position Information The APEX/APIC/SWAT+ modeling group at Texas A&M AgriLife Research is seeking a highly skilled and motivated Postdoctoral Research Associate to join a
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field. Documented experience in image reconstruction, inverse problems, signal processing, computational imaging, or cryo-EM data analysis is required. Strong programming skills (e.g., Python, C/C
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and digitizing archival data, strong knowledge of causal inference methods, good command of R and Python. Knowledge of machine learning methods is an asset. Strong command of English; command of either
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Postdoc in Decoding Biological Nitrification Inhibition (BNI) in Cereals: Integrating Metabolomic...
An ability to take initiative, develop, and manage research activities Proficient quantitative skills with data analysis and programming e.g. in R and python Documented experience in scientific writing and
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programming language (e.g., R, Python) Who we are At the Department of Agroecology, our main goal is to contribute to sustainable solutions to some of the world’s biggest problems within the areas of soil
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matter, biological physics and/or fluid mechanics. Experience of publishing in (or submitting to) journals of international standing. Programming skills, e.g. Python Strong oral and written communication
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, or a related field Strong experience in spatial and/or landscape modelling Proficiency in R and/or Python Experience with GIS and remote sensing Ability to work with large and heterogeneous datasets
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. Expertise in any of the following can be an advantage, but none is obligatory: Reproducible data analysis in R/Python/Julia Cell wall biochemistry Plant in vitroculture work In situmicroscopy and
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considering also the physical interactions between gesture and vocal production movements (e.g., breathing and articulation). The project looks at co-singing gesturing practices in three different vocal