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About the Role Applications are invited to join an ERC-funded research programme. The successful candidate will work at the interface of bioelectronics, mechanobiology, and disease modelling
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analysis, cell-state and cell–cell communication analysis, and predictive modeling. Lead secondary projects involving single-cell RNA sequencing and spatial transcriptomics. Perform raw-data processing
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that the successful applicant has experience in cardiovascular research and/or working with the zebrafish model. Experience of hPSC-derived in vitro models, 2D and/or 3D and experience in imaging, including use
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methodologies employed in modelling clinical cancer subtypes. Desirable: B1 Knowledge of molecular drivers of invasive prostate cancer and mechanisms of treatment resistance. B2 Knowledge and insight of different
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Engineering at Harvard University seeks outstanding postdoctoral applicants with expertise in non-human primate immunology and virology or analysis of spatial omics data to join an interdisciplinary team
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project focuses on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High
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limited to, large language models and foundation models, single cell analysis, spatial transcriptomics, multi-omics analysis, cancer research, intelligent healthcare, and precision medicine. Required
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analytical skills and experience with spatial modelling and statistical software such as R, Python, or MATLAB. Experience using GIS, side-scan sonar, multibeam bathymetry, underwater imagery, remote sensing
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with the University of Copenhagen, DiverCities, EIT Urban Mobility, Miljøpunkt Amager, and Trafik i Børnehøjde), which investigates how a care-centred, technology-enabled model of climate engagement can
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functionality in response to global changes and restoration efforts at large spatial and temporal scales is essential to understand where action is needed and to monitor restoration success. Developments in