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master's level courses in machine learning and R programming during the autumn semester of 2025 (with a possibility of extension). The main tasks involve assisting students during lab sessions and possibly
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, demonstrated experience of coding in programming languages such as R and Python is considered particularly advantageous. Examples of computationally intensive methods central to IAS and IDA are data-driven text
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(and the willingness to learn more), with an interest in biological/ecological questions; Experience with programming or the willingness to learn to program (the lab relies mostly on R and C++, but
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, demonstrated experience of coding in programming languages such as R and Python is considered particularly advantageous. Examples of computationally intensive methods central to IAS and IDA are data-driven text
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transfection work Experience with microscopy Experience with RNA-seq Experience with image and RNA-seq analysis, including competence using R or python and computational clusters Molecular biology techniques
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solid experience in coding with R, analysis of metabolomics and proteomics data, as well as in machine learning. You also need to have good knowledge of magnetic resonance spectroscopy and multiple