238 machine-learning-and-image-processing Postdoctoral research jobs at Nature Careers
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group (https://bckrlab.org). We focus on high impact applications and work on knowledge-centric AI and biomedical machine learning including multi-omics integration, single cell analysis, and sequential
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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. The lab is well-equipped: BioRad ChemiDoc MP gel imager, SpectraMax iD3 microplate reader, Dynamic light scattering instrument, Waters HPLC-MS, Waters prep-HPLC, ÄKTA oligonucleotide synthesizer, CLASS II
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, biomechanics, single cell-analyses, advanced imaging, and animal models. Tasks: to actively pursue the proposed project with the aim of characterizing the molecular, biomechanical and functional mechanisms
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of applications will continue until the position is filled. For instructions on the Interfolio application process, please visit http://tiny.cc/InterfolioHelp. Equal Employment Opportunity Statement The University
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motor behavior analysis. Technical experience with imaging, molecular biology, immunohistochemistry, in situ hybridization are also highly valued. Technical experience with embryo electroporation and /or
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; confocal/live‑cell imaging; high‑content analysis (microplate reader); ELISA/multiplex cytokine assays; qPCR/Western blot What we offer: Excellent infrastructure for materials synthesis/characterization and
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statistical analysis Competency in experimental design A strong desire to learn new techniques Should Have Either electrophysiology or imaging experience Skills Highly motivated Fluent in English Organizational
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in high-impact journals. Responsibilities Lead projects on developing novel analytical methods for studying the development and degeneration of the visual system Acquire, process, integrate, and
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, including finite-element simulation and topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks