27 genetic-algorithm-computer "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions at SUNY University at Buffalo
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Posting Details Position Information Fiscal Year 2024-2025 Position Title Postdoctoral Associate, Biomedical Informatics Department Classification Title Postdoctoral Associate Department Biomedical
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Posting Details Position Information Fiscal Year 2024-2025 Position Title Postdoctoral Associate (PRODiG+ Scholar), Computer Science Classification Title Postdoctoral Associate Department
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Posting Details Position Information Fiscal Year 2024-2025 Position Title Postdoctoral Associate, Biomedical Informatics Department Classification Title Postdoctoral Associate Department Biomedical
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using Pioneer-seq and genomics assays (e.g., ChIP-seq, ChIP-exo, MNase-seq, HiC, RNA-seq) Analyze high-throughput sequencing data and contribute to computational modeling of TF binding Outstanding
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projects include studying carbon metabolic pathways and genetic determinants underlying bacteria-phage interactions in Bacteroidales. Research projects leverage cutting-edge techniques, including DNA
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, biochemistry, or related field, demonstrated research productivity, and expertise in any of the following areas: microbial genetics, physiology & metabolism, analytical biochemistry (FPLC/HPLC/LC-MS/MS), animal
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(e.g. dopamine, norepinephrine) in the brain of living animals Use electrochemical microsensors coupled with genetic techniques Test animal behaviors (e.g. self-administration, anxiety-like behaviors
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Postdoctoral Research Opportunity: Lipid Biology, Cell Death, and Evolutionary Genomics. We are seeking a highly motivated Postdoctoral Associate to join our collaborative research program at the intersection
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cutting-edge genomics and computational analyses to investigate transcriptome, epigenome and chromatin architecture. Learn more: Our benefits , where we prioritize your well-being and success to enhance
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cutting-edge multi-omics at bulk, single-cell and spatial scales with computational analyses to investigate transcriptome, epigenome and chromatin architecture. Combine multi-omics with flow cytometry and