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Experience with machine learning and/or statistical modeling applied to biological data Proven expertise in single-cell data analysis (scRNA-seq and/or scATAC-seq) Interest or experience in multi-modal data
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which cells sense, adapt, and respond to their environment. We study free-living unicellular organisms as model systems. Using microscopy, quantitative measurements, and molecular perturbations, we seek
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to answer: How temporal and structural sparsity can be incorporated into the 3D dynamics reconstruction model? How sparse can a measurement be and still capture a high-resolution dynamic event? How do
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to answer: How temporal and structural sparsity can be incorporated into the 3D dynamics reconstruction model? How sparse can a measurement be and still capture a high-resolution dynamic event? How do
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models, acute brain-slice recordings, calcium imaging, and cancer research would also be particularly valuable. Applicants should also demonstrate a strong research track record, including at least one
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for bioinspired robotics. The main focus of this project is how neural circuits in the motor system of the fly, Drosophila melanogaster, orchestrate limb movements and autonomous behavior in complex environments