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Phenomic prediction programs that incorporates genotype (genotype by sequence) and phenotype data (from traditional and high throughput, remote sensing sources) -Use or develop R programming code to complete
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mechanisms impacting SOEC performance and lifetime Perform advanced EIS analysis (KK validation, DRT/DDT, CNLS, ECM/TLM modeling) Carry out electrochemical and thermodynamic calculations to support mechanistic
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 hour ago
. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). The Goddard Earth Observing System (GEOS), developed by NASA’s Global Modeling and Assimilation Office
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Argonne National Laboratory is seeking a highly skilled Postdoctoral Researcher to work in the Applied Materials Division (AMD). In this position the successful candidate will conduct applied
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functional analysis of soil biology. Utilize high-throughput sequencing technologies to analyze soil microbiomes and interpret the data using bioinformatics tools. Collaborate with interdisciplinary teams
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on finding and cultivating talented people who are passionate about what they do. Join us and be a part of the diverse Caltech community. Job Summary The candidate will conduct analysis and modeling
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extensive experience in: research with humans/biological samples; exome and variant analysis; Bulk RNAseq data analysis; immunoenzymatic assays (ELISA); structural bioinformatics (docking, modelling
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? No Offer Description Work environment: Research within the framework of a consortium funded by ANR ; Place of assignment: Faculty of Education, University of Montpellier Main mission: Data collection
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the framework of the ERC SYG project TOMATTO (The ultimate Time scale in Organic Molecular opto-electronics, the ATTOsecond), funded by the European Union (GA 951224). Activities to perform: Extend and use
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+ transients, voltage, contraction). To integrate our findings and generate new predictions and hypotheses, we aim to use multimodal deep learning and new systems analysis frameworks. Research area The