58 parallel-processing-bioinformatics-"https:" PhD positions at Forschungszentrum Jülich
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particles, depending on its polarity, aromaticity, and concentration Localization of the aromatic molecule within the initial lipid membrane as well as in the target membrane after the fusion process
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the characterization and operation of an NH4+/H3O+ chemical ionization time-of-flight mass spectrometer for measuring volatile organic compounds and organic aerosol composition Investigate photooxidation processes and
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research data management system and ontology Benchmarking state of the art materials as a baseline for the developed system Operation and further Development of an automated setup for catalyst inks and
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Your Job: Modeling and characterization at molecular level of selected biological processes by performing classical molecular dynamics, and employing enhanced sampling methods and machine learning
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covering the full spectrum of satellite instrument development: design, manufacturing, characterization, data processing, and scientific analysis Opportunities to present your work at national and
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Your Job: As a PhD candidate you will Use state-of-the-art methods to conduct gas- and aerosol-phase measurements, including the characterization and operation of an NH4+/H3O+ chemical ionization
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addition, the dynamics and transport processes across the UTLS adds complexity to unveil the role of UTLS aerosols in cirrus formation and the life cycle of cirrus. Therefore, it is crucial to measure
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promising lean alloy system for additive manufacturing, as the mechanical properties can be tailored through phase composition, distribution and morphology by tuning process parameters. The work is carried
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Your Job: Scientific analysis of additive manufacturing in the context of future production, material, and energy systems Research on the state of the art in additive manufacturing processes with a
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, data science, applied mathematics, physics, materials science, or a related field. Solid background in machine learning and/or computer vision. Interest in representation learning, active learning