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, diet, and immune system to investigate their roles in various diseases, including but not limited to cancer, metabolic disorders, and infections. The research design involves the integration of large
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Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...
products from the TanDEM-X radar mission, large airborne and field-based LiDAR datasets, and process-based models, as well as other openly available remote sensing and field datasets. The diverse data will
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The Peng Lab at the University of California, Los Angeles, is seeking highly motivated Postdoctoral Scholars with expertise in data science and bioinformatics to drive groundbreaking discoveries in
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analysis of biomedical data and bioscientific programming for a project on the study of neurological disorders. The candidate should have experience in the analysis of large-scale biomedical data (e.g
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, Experience and Qualifications PhD in biochemistry, Biomedical Sciences or Chemistry. Mass spectrometry-based proteomics. Data analysis of large proteomics datasets. Experience in cell culture and molecular
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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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sequence data for fungal plant pathogens within the Dothideomycete family. The lab has an existing fungal collection of over 40 strains collected from wheat, wild-grasses and barley. Ideal candidates will be
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training students Maintain analytical equipment Cooperate with other large collaborative projects of the research group Qualification: Required: A diploma and a PhD in microbial natural product chemistry
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of the extracts; LC-MS and bioactivity-guided isolation and structure elucidation of the purified metabolites Supervising and training students Maintain analytical equipment Cooperate with other large collaborative
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to self-organize into complex structures. Our approach is to develop sophisticated mathematical models – informed by state-of-the-art biological knowledge and experimental data – to understand