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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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both academic research and industrial applications. In addition to theoretical research, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation
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, miRNA, and proteome level from multiple lung compartments to construct a model of disease. The work will be conducted on one of several unique clinical cohorts designed to investigate different aspects
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in bioinformatics analysis and data visualization of our ongoing research projects on molecular characterization at the mRNA, miRNA, proteome and metabolome level from multiple lung compartments. Our
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and ability to work in an interdisciplinary and international environment Proficiency in written and spoken English. Meritorious Experience with multiple crystal growth techniques and/or diverse
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interdisciplinary and international environment Proficiency in written and spoken English. Meritorious Experience with multiple crystal growth techniques and/or diverse materials classes Familiarity with transport
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for a two year postdoctoral position to characterize the statistics of brain activity and relate it to the underlying network properties. Recent data has revealed the multiple ways brain activity
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skills, capable of managing multiple tasks and projects effectively. Excellent Communicator: Has strong verbal and written communication skills in English. Great emphasis will be placed on personal
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repertoire sequencing to examine vaccine-induced antibody and B cell responses in rituximab-treated multiple sclerosis patients across three doses of the BNT162b2 mRNA vaccine. The goal is to identify key
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letter: - Protein expression in prokaryotes and/or yeasts - Experience with multiple protein purification techniques - Development of recombinant protein production protocols