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the statistical analysis of neural data We offer A stimulating, international, interdisciplinary, collaborative, and supportive work environment, which emphasizes diversity and inclusion
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Immunology or Neuroimmunology Experience in working with mouse models (FELASA B or C required) Ability to adapt to the research environments while being full members of two labs Strong organizational and
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biology platforms for the sustainable production of high-value plant metabolites and 2) increased crop productivity by improvement of plant fitness in a changing environment. The research of the De Mey lab
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the lab environment and mentoring younger students. The postdoc will also gain the advantage of participating interdisciplinary collaborations, and should be eager about this, as it can broaden their
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to the wealth of information on both development and the dynamic changes due to environmental conditions; and the availability of many stage-specific marker lines and scRNA-seq data. There is however great
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and optimize experimental procedures. Adhere to safety protocols and maintain a clean and organized work environment. Qualifications Master’s or Bachelor's degree in plant Biology or related field
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term of 1 year, which may be extended by 1 year; Participation in an exciting and rapidly evolving new research area within a multidisciplinary environment; Become a member of a young, dynamic, and
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
, or related fields Strong programming skills in Python, R, and experience with Linux environments Demonstrated experience in processing and analyzing large-scale genomic and transcriptomic datasets
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epigenetic regulating circuits. CCB fosters an interdisciplinary environment and close collaboration with the Comprehensive Cancer Center LKI and the University Hospital, both located on the same campus
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ourselves on fostering an inclusive environment where diverse perspectives thrive, and people can feel free to disagree. Utilizing cutting-edge techniques like single-cell analysis, CRISPR technology, stem