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Field
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(Computer science, Statistics, Bioinformatics, Physics or similar fields) or in Life sciences with a strong computational and programming background, is required. All But Degree (ABD) status will also be
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. in Bioinformatics, Computational Biology, Data Science, Artificial Intelligence, or a related field. Proven experience in multi-omics data integration, omics data analysis (genomics, transcriptomics
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
present at international conferences. Mentor graduate students and contribute to building capacity in AI and health data science at UM6P. Required Qualifications: Ph.D. in Bioinformatics, Computational
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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responsibilities include bioinformatics analyses with a strong focus on single-cell RNA sequencing and next-generation single-cell barcode lineage tracing, as well as the interpretation of complex biological
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. in Basic Science, Health Science, or a related field. No experience required. Preferred Qualifications A Ph.D. in Genetics, Bioinformatics, Computational Biology, or a related field. Strong background
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a non-federal source. The position involves applying bioinformatic and statistical tools to existing multidimensional datasets, including metagenomic, transcriptomic, proteomic, and metabolomic
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bioinformatics methods have made significant strides, AI approaches - particularly deep learning - are revealing patterns and relationships in biological data that were previously inaccessible. As a postdoctoral
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well as bioinformatics and bacterial imaging. Main Duties and Responsibilities Perform the following activities in conjunction with and under the guidance of the Principal Investigators (PI): 1. Plan and conduct assigned
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analyses of viral proteins using AI-based prediction tools will also be integrated to support evolutionary inference. This work lies at the intersection of evolutionary biology, bioinformatics, and data