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Field
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Köhler Lab, Max Perutz Labs, Vienna BioCenter Rethinking cellular boundaries Cellular boundaries are not passive—they are interfaces that convert spatial separation into function. Membranes, nuclear
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contributing to specifically the area of handling spatial data to assess the distribution of several soil properties and fungal communities using samples collected from multiple habitats and land use types at a
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datasets. Your focus will be on implementing and training generative models to decompose cylindrical projections. You will solve and refine the structures from the resulting decomposed data. You will map
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diversity and dynamics of metabolic states in retinal ganglion cells; spatial transcriptomic and correlated metabolic analysis of retinal ganglion cells; treatment of retinal ganglion cells in models
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the following directions: 1) Developing computational methods for integrating multi-modal data, such as scRNA-seq, scATAC-seq, spatial transcriptomics, ChIP-seq, and CRISPR screening. 2) Investigating context
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have expertise in working with animal disease models, single-cell and spatial RNA sequencing technology, and a solid understanding of the CNS immune landscape. Additionally, applicants should have at
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required Experience analyzing wearable device data including accelerometer and GPS data, as well as experience with spatial data analysis Demonstrated publication record in high quality peer-reviewed
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lead experimental efforts using advanced nanoscale optical and scanning probe techniques—including spatially and temporally resolved photoluminescence, electroluminescence, and a strong focus on
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sequencing data from up to 10,000 trees. We are using birches (Betula) as our model organism, as they have a relatively small genome, they are adapted to their local environments and there are accelerated
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] that process information in temporal rather than spatial modes to reduce their footprint. The project involves a collaboration between DTU Electro (Senior Researcher Mikkel Heuck) and Harvard University (Dr