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Field
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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and
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applications. Research activities may involve geophysical forward modeling, AI-driven geophysical inversion, seismic monitoring and imaging, scientific machine learning, depending on the specific research focus
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: experience working with spatial omics or spatially resolved data in tissue experience applying AI or machine learning methods to digital pathology or histology data experience analysing kidney or transplant
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engineering (CRISPR/Cas9, Gal4/UAS), including the generation of genetic tools in non-model Drosophila species; single-cell genomics (scRNA-seq and single-cell ATAC-seq); in vivo functional imaging (two-photon
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learning (ML). Our lab explores the intersection of artificial intelligence, and human-computer interaction, striving to create technologies that amplify human potential. The successful candidate will engage
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with neuroimaging and neural signal processing tools, including fMRI, structural MRI, diffusion MRI, EEG, or related modalities. Strong publication record in AI, machine learning, computational
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at NeuroSpin is very scientifically stimulating, combining MRI physicists, machine learning experts, and cognitive neuroscientists. Team members go there to collect data and collaborate with their colleagues in
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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against different operation conditions. The position is a part of a research project and prototype battery modules will be produced by one of the partners. The tasks include testing of these prototype
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acquire new technical expertise as needed. Participate in clinical research efforts involving retrieval, processing, and molecular analysis of patient-derived specimens from prospective clinical trials