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Field
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an opportunity to network and get feedback on their work. Student profile: Some experience in data analysis would be very helpful, as would a working familiarity with a programming language (e.g. Python, R
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. Strong quantitative skills, with experience in econometrics and statistical analysis. Experience working with large datasets and appropriate software (e.g., Stata, R, Python, Julia, MATLAB). Excellent
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(e.g., Python, or MATLAB, or C++; knowledge in ROS). Interest in robot control, learning, manipulation, and task planning. Preferred Experience with robotic hardware or simulation tools. Publications in
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of the position. Equivalent research experience will also be considered. You should have familiarity in handling large and complex datasets and skilled in programming languages such as R or Python. The ideal
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/ physics/ meteorology/ engineering/ biology. Experience in a computer programming language (e.g. Fortran, Python). A general understanding of the importance of the scientific method is essential. A previous
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degree in Engineering and have an interest in and/or a good understanding of numerical modelling and testing of structures. Prior knowledge of finite element methods and programming (e.g. C++, Python
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combination of overseas field work (Europe and other locations), image based and laboratory work to characterise soil properties to address the questions above. The imaging work will be a combination of GIS
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the questions above. The imaging work will be a combination of GIS mapping of sites and X-ray Computed Tomography of soil samples. Full training will be given for all aspects of the work and strict health and
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is