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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
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institutions, along with a team of new postdocs, to explore the many facets of biological invasions by plants, insects, and tree pathogens in forests worldwide. The activities of FISC are conducted in
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or spatial transcriptomic data analysis Candidates who are nearing completion of their PhD may apply, but confirmation on awarded PhD is required within 6 months of employment. The ICR has a workforce
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on advancing the understanding of ophthalmic diseases through innovative multiomics approaches and bioinformatics. The postdoc will engage in interdisciplinary collaborations to drive novel research initiatives
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, or forest management. Project Overview The postdoc will contribute to the Silva21 research program, which aims to develop innovative strategies to enhance the resilience of Canadian forests in the face of
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of T1D, human translational studies, and innovative technologies including spatial transcriptomics, single cell RNA-sequencing, and induced-pluripotent stem cells, we are interested in determining how
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contribution of 17% superannuation applies. Fixed term position for 24 Months. Postdoc opportunity - Open for Applications Until Filled. We are seeking a dynamic and motivated Postdoctoral Fellow in Ecological
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computational modeling, geometric morphometrics, multivariate and Bayesian statistics, spatiotemporal and spatial modeling (including GIS), causal inference, machine learning, AI, and statistical software