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Field
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large-scale datasets of genetic circuit designs and dynamic single-cell behaviors. These datasets will be used to train multi-scale AI models that learn how genetic circuit designs produce cellular
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(postdoc) Limited until: 31.10.2032 Reference no.: 6212 There are many good reasons to want to research and teach at the University of Vienna. And one is why around 7,700 academic staff members before you
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technological landscape continuously inspires innovation, are you keen to uncover the student perspective, and the implications of AI for meaningful student learning? Job description Delft University
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, brain organoids, genome editing, high-resolution imaging, single-cell sequencing, spatial transcriptomics, epigenomics, and proteomics, as well as a unique mouse model in which neural progenitors acquire
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/ lentiviral transduction, transposition, CRISPR-Cas9). Viral particle assembly. Excellent aseptic cell culture technique. Enthusiasm and a willingness to learn in a fast-pace, collaborative environment. Strong
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, genomics, or computational analysis of high-dimensional datasets. Experience with one or more of the following: Flow cytometry Single-cell sequencing Spatial transcriptomics Multiplex imaging Bioinformatics
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project TARGETWISE. The candidate will be responsible for conducting machine learning omics data analysis within the computational team. The details on responsibilities, obligations and rights
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Liu Lab · Department of Cell Biology · Yale School of Medicine Title of Position Postdoctoral Associate in ER Metabolism and Organelle Biology Department and School Department of Cell Biology, Yale
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across tissues, over time and upon perturbation for translational benefit, leveraging tissue profiling through multiomic technologies in conjunction with cutting-edge computational and machine learning
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-cell or spatial transcriptomic analysis is desirable. Experience with machine learning, LLMs, AI agents, multimodal data integration, or automated biological interpretation workflows is desirable but not