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in non-parametric, 3D environment modelling. We will assess the utility of these tools for map-building using magnetometer data as well as exploring the potential for existing geospatial maps to enable
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models, and efficient algorithms for large-scale genomic data analysis. This is a one-year appointment starting as early as possible, with renewal possible based on the availability of funds, availability
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science, machine learning, AI, or any computational science discipline of interest to the Computing Sciences Area and Berkeley Lab. Fellows apply advances in these fields to computational modeling
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multi-parameter flow cytometry Expertise in molecular immunology using human specimens, including controlled human infection models Expertise in liver-stage immunity Expertise in host-pathogen
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: emerging mobility, mixed traffic modelling, connected and automated vehicles, micromobility, experimental design using driving simulators, virtual reality (VR) and augmented virtual testing, and test tracks
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. Working within a collaborative, supportive, and industry-connected research environment, you will contribute to applied research that advances soft sensor development, process modelling, comminution, and
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, network analysis, and mathematical modelling — with opportunities to pursue independent research. Curious to learn more? Read further to discover more about this opportunity. The team The successful
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area of Gaussian Process based Simultaneous Localisation and Mapping (SLAM) and recent advances in non-parametric, 3D environment modelling. We will assess the utility of these tools for map-building
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/knowledge: Experience in lab or synchrotron x-ray reflectometry techniques and fitting data to existing models. Interest or experience in instrumentation development. Experience in condensed matter material
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to more than one; state your preference in your motivation letter. 1. Neurodevelopmental proteomics You will map the molecular circuitry of human neurodevelopment using advanced 2D and 3D cell models together