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(e.g., R, Python). Proven ability to publish at a high international level. It is a prerequisite that you are good at communicating in English. Strong collaborative skills and good collaboration skills
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for applicants to demonstrate proficiency in at least one scientific programming environment such as Python, MATLAB, or R. Good understanding of hydrodynamic loading and wave–current environments (e.g., wave
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software skills Proven experience with CFD automation, e.g. using PyFluent or similar Python APIs for meshing, solver control, post-processing and data management. Solid experience programming in Python
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languages such as Python or R. Experience with machine learning, systems biology, or network modeling approaches. Previous expertise in human cardiometabolic or complex diseases, with domain expertise in but
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and Python are required. The successful candidate will be based in Odense, under the primary supervision of Prof. Stefan Jänicke. The appointment will be made for 2 (two) years at a competitive salary
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Stata; Knowledge of R, Matlab, Python, and/or Fortran; Experience working with micro data, ideally administrative or matched employer–employee data; Documented research track record at international level
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qualifications: Strong experience in programming using Python, R, or other languages Research experience in remote sensing of cover crop, crop type classification, and crop biomass Insight into global
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with AI/ML implementation, particularly for sensor data processing, feature learning, or autonomous system control Solid software development skills in languages such as Python, C/C++, or similar, with
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
field Knowledge of freshwater ecology and/or physical limnology Experience with numerical modelling Experience with programming languages, esp. Python, and familiarity in NumPy, SciPy and Pandas
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assessments. Key responsibilities Design and conduct experiments. Operate and maintain gas measurement equipment and flux chambers. Process, analyze, and visualize large data sets using Matlab, R, Python