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center for artificial intelligence in life sciences, we benefit from high-throughput computing infrastructure to support advanced data analysis and integration. Profile We are looking for a motivated
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for the design of synthetic promoters and data analysis. PhD in (Plant) Biotechnology, Molecular Biology, Biochemistry or equivalent A publication record in peer-reviewed journals, and excellent proficiency in
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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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will focus on the development, optimization and application of multi-modal analysis strategies and pipelines for sequencing data generated on nucleic acids isolated from biofluids (genomics, epigenomics
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their impact on bladder function under physiological and pathological conditions. Work will include data acquisition, analysis, and interpretation, as well as collaboration with clinicians for human
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Excellent communication skills in English Desirable but not required Skills in phytoplankton genetic engineering Hands-on experience with high resolution mass spectrometers and/or data analysis Programming
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Post-doc eligibility criteria Required Skills Minimum 3 years hands on experience with complex flow cytometry is required, including panel design, testing, troubleshooting and analysis Experience in
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also opens new avenues for the design of climate-resilient crops. You will apply AI strategies to learn the regulatory syntax encoded by the Arabidopsis genome using single-cell transcript data as
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. The names and contact details of 2-3 referees. For more information, please contact Dr. Sibylle Vonesch (sibylle.vonesch@kuleuven.be ) (only clarifications or further details regarding the vacancy
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Polleux, Nat. Rev. Neurosci. 2023). You will explore single-cell epigenomics and transcriptomics data, focused on the neurons of the cerebral cortex from human and an array of non-human species. Using