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Field
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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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automated data pipelines and flexible toolsets to support diverse microscopy-based research projects, including the integration of multimodal datasets (e. g., imaging, omics and spatial omics) Serve as the
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learning frameworks such as PyTorch or TensorFlow is an advantage); Affinity with probabilistic modelling and spatial data analysis; Interest in the physical behaviour of water systems and hydrology (prior
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drugs. Our focus is on cytokine-based drugs and immune checkpoint inhibitors. We use immune competent murine models and human cell culture systems for early drug development. We also study mechanisms
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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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the dynamics of therapy-resistance by combining advanced molecular biology method development to multi-omic single-cell analyses of both ex vivo models and clinical tumor specimens. Our novel, in-house
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into clinically deployable diagnostic and prognostic tools. The successful candidate will contribute to the development of a spatially resolved 3D atlas of the bone marrow, advancing precision diagnostics in blood
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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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students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration
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(plant) molecular genetics, microscopy, and cell biology are required. Previous experience with model grass species, (plant) signalling, protein biochemistry, or single-cell/spatial transcriptomics is an