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. Expertise in any of the following can be an advantage, but none is obligatory: Reproducible data analysis in R/Python/Julia Cell wall biochemistry Plant in vitroculture work In situmicroscopy and
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Python, and used to working with large datasets and reproducible analysis workflows. Has a demonstrated ability to initiate and drive own research ideas, preferably with experience from writing and
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to be able to independently develop scientific concepts and methods, be competent in coding with Python and Matlab at least, and be fluent in both speaking and writing in English. The EU Mobility Rule
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scans. Experience with age-depth modelling (c14 dates, stratigraphic correlation). Experience with Python or similar programming language. Documented very good oral and written proficiency in English
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before the fellowship decision date. Documented experience in research projects within the scope of the awarded degree. Required competencies: Strong background in bioinformatics (e.g., R, Linux, Python
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experience with work with human cancer cell lines, stem cells, and/or immunohistochemistry is a plus Programming skills with Python or R is a plus Excellent communication skills A solid experimental or
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experience, familiarity with computational analysis (Python or R and HPC environments), and a strong interest in DNA repair, chromosome biology, meiosis, or genome stability. Experience in DNA repair assays
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high-dimensional biological data and programming languages (Python) is considered a merit Ability to work independently, plan experiments, and troubleshoot complex experimental workflows Strong
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Comprehensive skills in data analysis and bioinformatics Proficiency in programming with Python Proficiency in version control (Git, GitHub) Meriting criteria are: Experience in mechanistic and ODE-based
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requirements: Very good oral and written proficiency in English. Ability to drive and independently progress the project Strong computational skills with considerable experience with programming with python