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skilled in data analysis with proven experience with programming, e.g. Python Be skilled in experimental work Previous experience with microscopy is an advantage but not required. You must have a two-year
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learning, statistical analysis, and other contemporary data-driven techniques. Computational methods such as optimization, filtering algorithms, predictors, etc. Software and coding skills with, e.g., Python
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contemporary data-driven techniques. Computational methods such as optimization, filtering algorithms, predictors, etc. Software and coding skills with, e.g., Python, MATLAB, R, C++, Julia, potentially HIL
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an assessment of relevant methodological approaches. Applicants should furthermore: be able to demonstrate excellent quantitative and coding skills, particularly in R or Python. have a commitment to building on
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and statistics: Python, R, MATLAB Strong English communication skills; both written and orally Experience with any of the following is appreciated. mySQL, computational workflow managers, clustering
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experience in theoretical condensed matter physics, especially in ab initio simulations for materials (preferred). Be proficient in scientific programming (preferably Python) and comfortable working with
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quantitative methods Experience in one or more programing languages (e.g. R, Python) Knowledge of public health, foodborne disease surveillance, and animal disease surveillance is an advantage Excellent
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degree in electronics, robotics, autonomous systems, or a related field. Software skills in ROS, Python, and C++ and graphic user interfaces using VR/mixed reality. Good academic writing skills
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suited for data science and statistics: Python, R, MATLAB Strong English communication skills; both written and orally Experience with any of the following is appreciated. mySQL, computational workflow
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using Python. General knowledge in carbohydrate chemistry and enzyme technology, i.e. carbohydrate structures and terminology. Strong analytical and problem-solving skills. Ability to work collaboratively