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with major research universities worldwide as well as with neuro-related industries. Job Description Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found
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transfer (CHT) or fluidic manifold optimization Experience with machine learning/AI (PyTorch or TensorFlow), reduced-order modeling (ROM), or data assimilation (DA) Experience with GPU programming (CUDA and
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limited to: systems design; critical design, making, and fabulation; arts-based or critical engineering methodologies; sociotechnical systems design drawing upon anthropological, sociological, or STS
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, Cancer Biology, or a related field. Preferred Qualifications: • Strong background in cancer biology and immunology, with expertise in cellular immunotherapy techniques (e.g., CAR-T cell therapy, TCR
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required to meet the eligibility criteria. Of secondary importance are: Experience with Python and relevant libraries for machine learning, optimization and simulation. Documented expertise in simulation
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a novel multi-omics approach that integrates high-throughput imaging and machine learning methods with CRISPR/Cas9 screens and saturation mutagenesis to answer central questions about the
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the use of machine learning and AI approaches • Integration of proteomics with genetic data via MR, coloc and FUSION to identify causal and druggable targets Requirements • The successful applicant will
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, ventriculomegaly). Experience in machine learning statistical methods. Experience in the acquisition of infant neuroimaging data. Prior experience working with infants and children in a research setting. Enthusiasm
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website: https://cruchagalab.wustl.edu/ . Research Projects: Plasma, CSF and Brain Proteomic analysis. Biomarker identification through the use of machine learning and AI approaches. Integration
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Integrate multi-omics data with clinical, cognitive, and imaging phenotypes in longitudinal cohorts Develop and apply statistical and machine-learning models (e.g., mixed-effects models, survival analysis