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Field
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research. Experience with advanced techniques such as flow cytometry, imaging, genomics, or bioinformatics. Ability to work both independently and collaboratively in a multidisciplinary research environment
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About You Essential Completion of a PhD in infectious disease epidemiology, veterinary science, animal science, immunology, bioinformatics, or a closely related discipline. Demonstrated postdoctoral
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externally (e.g., conferences) Required: PhD in Bioinformatics, Computer Science, Computational Biology, or related field Experience analyzing DNA sequencing data Proficiency in Python and/or R Familiarity
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faculty specialising in Biostatistics, Bioinformatics, Systems Biology, Artificial Intelligence (AI), and other quantitative and data-driven sciences. CBDS functions as a strategic platform for cutting-edge
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to independently work in a collaborative research environment are required. Preference will be given to individuals with hands-on experience in RNA and/or epigenetic technologies. Bioinformatics or animal management
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) Mammalian cell culture (experience with induced pluripotent stem cells and/or adult stem cells preferred) Machine learning and basic bioinformatics A proven solid research experience in the context of multi
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involved in the bioinformatic and analytic aspects of predictive modeling. MINIMUM JOB QUALIFICATIONS: A Ph.D. in bioinformatics, genetics, statistics, mathematical, physical, or computer science
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of cancer research and are located in Heidelberg/Mannheim, Dresden, Mainz and Würzburg. Available cancer research areas include: Biochemistry Bioinformatics and Computational Biology Cancer biomarkers and
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; 2024.16864.PEX, financed by national funds through the Portuguese foundation for Science and Technology (FCT I.P.), under the following conditions: Scientific Area: Bioinformatics Recipient category: The open
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epidemiology, bioinformatics, computational biology). Candidates who have successfully defended their thesis or dissertation are welcome, subject to evaluation on a case-by-case basis. Experience analyzing large