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Field
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selection criteria Experience with behavioural-related experimental work Knowledge on programming in R/Python is beneficial Personal characteristics To complete a doctoral degree (PhD), it is important that
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strong computational skills, including programming (Python or similar), data analysis, and familiarity with machine learning for time-series and sensor data. Basic knowledge of designing and building
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Python) and data analysis or machine learning applied to materials science Ability to work in interdisciplinary project or industrial experience About the employment The employment is a temporary position
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. Desirable Skills (an advantage, not a requirement) Data analysis skills in python. An interest in energy policy / the economics of energy. Numerical modelling. Eligibility This studentship is available for UK
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/teaching experience. The confidence to deal with uncertainty and tackle any problem without a defined final answer. Desirable Skills (an advantage, not a requirement) Data analysis skills in python. Granular
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at least one scientific programming environment such as Python, MATLAB, or R. Familiarity with structural degradation phenomena—including fatigue, corrosion, and biofouling—would also be beneficial
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Python (or equivalent). Experience with glass science, battery materials and/or atomistic simulations is highly advantageous. All interested candidates are encouraged to apply, regardless of their personal
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programming in R or Python; affinity with scientific writing, preferably demonstrated through prior experience; excellent written and oral communication skills in English. Experience with genetic analyses and
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programming skills and expertise, e.g., Python, Julia, C/C++ Willingness to work independently and contribute to lidar soundings duringnights/weekends in accordance with applicable working laws. Communication
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scientific programming, e.g. using Python, is expected. As we work in international environment it is important that you have a good communication skills in both spoken and written English, and experience in