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Davoud Torkamaneh

Professor

Université Laval

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United States

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Chemistry

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Genomic

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Biology

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Machine Learning

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Agriculture

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Positions1

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Davoud Torkamaneh

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Université Laval

Fully Funded Postdoctoral Position in Plant Metabolomics and Multi-Omics Integration at Université Laval

Université Laval in Québec, Canada, is offering a fully funded 2-year postdoctoral position in metabolomics, focusing on plant specialized metabolites and multi-omics integration. The successful candidate will join a dynamic, interdisciplinary team with access to top-tier research facilities at INAF, IBIS, and IID. The research will involve developing and applying advanced metabolomics workflows (targeted and untargeted HPLC/GC-based approaches), integrating these with genomic, transcriptomic (RNA-seq), and phenotypic datasets. The goal is to advance genetic and metabolic engineering strategies for enhanced production of specialized metabolites, precision phenotyping, and trait improvement in plants, bridging metabolomic insights with experimental biology for sustainable agriculture and biotechnology applications. The position offers a competitive salary of $60,000 CAD per year (negotiable), full benefits, and comprehensive research support. Applicants must have a PhD in Metabolomics, Computational Biology, Analytical Chemistry, Plant Biology, or a closely related field. Required skills include strong experience in metabolomics data generation and analysis, proficiency with large-scale HPLC and GC datasets, advanced programming skills in Python and/or R, and experience with tools such as XCMS, MZmine, MetaboAnalyst, Bioconductor, or TensorFlow/PyTorch. A strong publication record in metabolomics, multi-omics integration, or plant specialized metabolism is expected. Familiarity with mass spectrometry-based metabolomics, pathway/network analysis tools, and machine learning for biological data is an asset. The position is open to domestic candidates only due to the immediate start date. Key responsibilities include developing and implementing advanced pipelines for metabolomics data processing, applying statistical, multivariate, and machine learning approaches to uncover regulatory networks and genotype-metabolite-phenotype associations, collaborating on multi-omics integration strategies, and publishing high-impact research in peer-reviewed journals. The successful candidate will also contribute to grant applications and present findings at international conferences. To apply, candidates should email their CV, a 1-2 page research statement detailing their experience in metabolomics analysis and multi-omics integration (with specific examples of tools, datasets, platforms, or projects), copies of key publications, and contact information for two references to [email protected]. Applications will be reviewed on a rolling basis until the position is filled. For more information, visit the supervisor's LinkedIn or academic page .