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with Western blot analysis is considered an advantage. Bioinformatics skills, including basic data processing, statistical analysis, or work with high-throughput or sequencing data, are highly welcome
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description The project will use bioinformatic analysis together with comparative approaches to individual cells, and machine learning to investigate how the vertebrate head evolved and what mechanisms control
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microscopy, CRISPR, omics approaches (Chip-seq, proteomics), or bioinformatics. How to apply: Cover letter: your motivation to apply for this position and description of your research interests. CV: Highlight
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transformation, or reporter-based imaging basic data analysis skills (R/Python), statistics, or omics/bioinformatics prior experience with hormone biology/plant signalling/transport LanguagesENGLISHLevelGood
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, bioinformatics, or a related field Strong track record shown by publications in peer-reviewed international journals Hands-on experience with single-cell and/or spatial omics analysis (scRNAseq preferred
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income of the CEITEC PhD School student is expected to be at least CZK 29,400 (approx. EUR 1215) Requirements for candidate: Background in molecular biology, biochemistry, or life sciences. Interest in bioinformatics
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, bioinformatics, or a related field Strong track record shown by publications in peer-reviewed international journals Hands-on experience with single-cell and/or spatial omics analysis (scRNAseq preferred
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bioinformatics Ability to work on a multidisciplinary project involving fieldwork, lab work and computational analysis Benefits: 5 weeks of paid holiday yearly, subsidized lunches in our own canteen Pension
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genetics, molecular biology, and bioinformatics will be greatly advantageous Display exceptional communication abilities and a collaborative spirit Demonstrate strong organizational skills Include these in
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Biology, Machine Learning, Bioinformatics, Biotechnology or related discipline Experience with computational tools for protein engineering or machine learning Demonstrated ability in biological data