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possible. Applicant Profile Applicants should have a university degree in physics, physical chemistry, or biophysics (or near completion). Experience with computational science, programming (C/C++ or Python
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academic writing. • You should have experience with the usual tools for advanced experiments: programming experience: Matlab, Python, LaTeX. • You have excellent command of written and spoken English. What
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meteorology, physics, geosciences or related field excellent programming skills (preferably in FORTRAN or Python) interest in interdisciplinary climate and coastal research We offer you an exciting and varied
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simulation models Programming skills (e.g. Matlab or Python) Willingness to supervise young scientists Enthusiasm and enjoyment of working independently on developing fresh ideas and solutions Good
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(preferably in R, Python, GIS) • Competences in quantitative research methods - ideally knowledge of several of the following aspects of quantitative data analysis: analysis of large/longitudinal datasets
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in at least one major programming language, such as Python, is expected Familiarity with deep learning frameworks and modern NLP toolkits is an advantage Motivation to publish research results in
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of Unix systems (GNU Linux) and keen to gain hands-on experience in Networks and systems Machine Learning knowledge is a plus Strong analytical and programming skills are required (Python, Matlab, Golang
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learning - deep neural network, recurrent neural network, LSTM Optimization theory Stochastic geometry Strong programming skills in at least one of the following: MATLAB, Python, JULIA or C++ Language
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in Python. Interest in (or prior exposure to) metamaterials / architected materials (e.g., lattices, TPMS, graded microstructures) and homogenisation concepts. Basic understanding of anisotropy and
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and their development Strong analytical, problem solver, and programming skills, e.g. Python, Matlab, are preferred Knowledge in Non-Terrestrial Networks and Semantic Communications is a plus Prior