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Your Job: Analysis and integration of diverse biological data from the field of plant sciences (large scale genomic, transcriptomic, proteomic, metabolomic and/or single cell data) using cutting
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, simulation of the vacuum conditions and heat management during operation, estimation of the pumping capacities including engineering of the pumping stations, gauges and valves, define the operating and system
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machine learning-based software applications for materials science Develop code and utilize machine learning to support the automation of characterization and fabrication processes Ensure the integration
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addition to technical models allowing to assess technical scaling and an optimal operation. The optimal plant design is identified by considering the energy supply system, the choice of capture technology, the DAC
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data collection and metadata extraction protocols to enhance machine learning-based software applications for materials science. Your Profile: Master’s degree in Engineering, Computer Science, Physics
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/electronic engineering, computer science, computer engineering, physics, and related fields. For IC projects a strong electronics background, with experience in design and simulation of analog, digital
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Infrastructure? No Offer Description Work group: IAS-9 - Materials Data Science and Informatics Area of research: Promotion Job description: Your Job: You will strengthen the data science and machine learning
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plant design is identified by considering the energy supply system, the choice of capture technology, the DAC-plant’s technical design, the DAC-plant’s operational concept and the positioning of the DAC
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Your Job: You will strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists
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: https://www.fz-juelich.de/profile/frunzke_j Your Profile: Highly motivated and excellent candidates with a Master of Science degree in biology, biochemistry or related subjects are strongly encouraged