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mass spectrometry (especially GC-MS) and programming (e.g. R), statistical knowledge for omic-scale research questions Scientific publishing experience in renowned, subject-relevant peer-reviewed
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related discipline and have begun to establish a strong research profile, evidenced by a strong, well-cited publication record. Proficient in Python, R, BASH and/or other relevant programming languages, you
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in Environmental Modelling, Land Use modelling or another relevant field, with clear skills highly complementary to those of the JPP4JL research team Proven ability to write code in R or python
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competitiveness in GM. AMMIC brings together world leading research facilities and expertise to stimulate new investment in research and development (R&D) to address regional and national materials and
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of statistical programs (e.g. in Matlab, R or SPSS) German and English skills Proven ability to collaborate effectively, maintain performance under tight deadlines, and demonstrate a high level of commitment and
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knowledge of statistics (R) Experience with multiverse analysis and open science practices Experience in the measurement and evaluation of eye tracking data is desirable Experience with physiological data
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with R or Python tools. Experience in processing of targeted and untargeted mass spectrometry datasets Demonstrated research competence and initiative through inernational publications in peer-reviewed
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R