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of using Python or R Very good written and spoken English (min. B2) In addition, the following criteria are desirable: basic knowledge of analytical chemistry, neurobiology, or behavioural ecology Experience
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; Experience with programming (e.g. Python) is a plus; Familiarity with membrane biophysics or soft matter physics is advantageous; Strong written and oral communication skills in English; Ability to work
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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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, bioinformatics, computational biology, statistics, computer science, or similar Solid programming in R and/or Python, and/or experience analyzing sequencing data in a bioinformatics context Preferred Prior work
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in R and/or Python, and/or experience analyzing sequencing data in a bioinformatics context Preferred Prior work with single-cell RNA-seq (QC, normalization/integration, differential expression
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-authored peer reviewed papers) • Well-developed statistical software skills (preferably in R, Python, GIS) • Competences in quantitative research methods – ideally knowledge of several of the following
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for research. What we are looking for MSc in computer science, statistics, or a related quantitative field Proficiency in Python and experience with PyTorch, TensorFlow, or JAX Demonstrated ability to complete
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Proficiency in Python and experience with PyTorch, TensorFlow, or JAX Demonstrated ability to complete technical projects (thesis, publication, or GitHub repo) Familiarity with clinical data is helpful but not
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. This position will be part of the Environmental Psychology research group (see https://env-psy.univie.ac.at/about-us/) and will be supervised by Profs Sabine Pahl and Alexandra Brausmann (environmental economics
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. For additional information, please visit: https://dakic.univie.ac.at/ . Your future tasks: You will actively participate in research, teaching and administration. This means: • You are involved in a well-funded