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by immunoassays and immunoprecipitation to prioritize candidate exo-proteins for the ovarian cancer “fingerprint” that can differentiate HGSOC from controls and other ovarian cancer patients
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, single-cell multiomics, tissue engineering, and animal models. Our current research primarily focuses on four key areas: 1) Developing robust, chemically defined differentiation protocols to generate
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), along with detailed clinical and behavioral data, we are scaling up analytic efforts to answer fundamental questions about how grief unfolds over time—especially in older adults—and what differentiates
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an innovative glial cell-based therapy capable of repairing the injured spinal cord and the corticospinal tract (CST) through axonal growth, oligodendrocyte differentiation, and remyelination to maximize
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thymic tissues to develop a robust in vitro and in vivo developmental model of thymic development. This model can now be applied to differentiating iPSCs into regenerative thymic tissues for clinical
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architectures and training algorithms, uncertainty quantification, high-dimensional stochastic systems and high-dimensional partial differential equation systems. Multiple positions available. About the T-5 Group
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with physics-informed neural networks, automatic differentiation, neural ODEs, or other physics-aware DL techniques. Skill in programming languages such as Python, C/C++, Go, Rust etc. Ability to model
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. ● Experience with neuronal and/or microglia differentiation using iPSCs. ● Experience culturing and assaying neuronal cultures (human iPSC-derived neurons). ● Experience with immunocytochemistry, confocal
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focuses are: 1) Investigating the underlying molecular mechanisms by which 3D genome topology controls the hematopoietic transcription program and lineage differentiation in normal and malignant
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/10.1016/j.isci.2022.104225 ), their 3D organization in the bone marrow, and the cell-to-cell interactions that define cell differentiation. Furthermore, we are investigating – through the same technologies