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streams over time based on real-time achievement and applications are the key part of the research. The Postdoctoral Fellow will use building simulation tools and programming tools such as MATLAB or Python
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(IRT) models in small samples. The ideal candidate has prior knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant
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System (ROMS) experience with modelling of marine sediments programming skills in FORTRAN, MATLAB and/or Python experience with super-computers and with the Linux environment an established publication
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. Experience with cell type specific interactions is an advantage. Experience in other programming languages than Python is an advantage. Statistical knowledge (survival analyses, linear regression, etc.) is an
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other programming languages than Python is an advantage. Statistical knowledge (survival analyses, linear regression, etc.) is an advantage. Working experience in interdisciplinary teams (i.e. in medicine
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planetary science instruments The Post Doc candidate must have experience in Python programming The Post Doc candidate must be eligible to be able to join the NASA Mars 2020 Science Team. The Post Doc
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. Previous programming experience (C++, Python or Fortran are the most relevant languages). Experience with modern coding workflow, and in particular revision control, and code testing. Previous experience
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knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant computing language. Experience with machine learning methods is a
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. Experience in scientific programming (e.g., Matlab and Python) is a requirement. Experience with analysis of climate data sets is an advantage. Applicants must be able to work independently and in a structured
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and Python) is a requirement. Experience with analysis of climate data sets is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative