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team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed
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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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cell molecular analyses, and in vivo time lapse. The ideal candidate will have experience in molecular biology as documented through their publication record. Prior expertise in the application of genome
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und der Länder (VBL). In-house support for Fellowship applications. Work-life balance (certified by Audit Beruf und Familie) as well as flexible working hours and the possibility of mobile working
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development of blood malignancies and other solid cancers. Our research bridges basic, translational, and clinical studies to uncover mechanisms linking inflammation, DNA damage, and stem cell aging to cancer
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and computational research in plant molecular and cell biology; analyze data obtained; prepare presentations and manuscripts for publication. Required Minimum Qualifications: PhD in biochemistry
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Chart tumour evolution using cutting-edge long-read and single-cell multiomics Who we are The Integrative Cancer Genomics lab (Jonas Demeulemeester) is embedded within the VIB – KU Leuven Center
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, genome editing, drug screening etc., with the use of primary patient’s samples and cell lines. The research might bring new insights into the microenvironmental dependencies and development of resistance
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lead the development and application of advanced microscopy techniques, microfluidic approaches, and single-cell analysis methods to investigate quiescence at individual cell and population levels. Where
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molecular biology technics. Furthermore, we developed a novel co-culture model inducing robust primary CLL cell proliferation (~50%) in vitro (Hoferkova et al, Leukemia, 2024). We aim to utilize this game