15 image-processing-and-machine-learning "UCL" Postdoctoral positions at New York University
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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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vision, controls, cyber-physical systems and their security, hardware security, and machine learning and their security. The work will include algorithm design, prototype implementation (e.g., in Matlab
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signaling in larval Drosophila using two-photon tracking microscopy developed in the Gershow lab. The postdoctoral researcher will design and conduct imaging experiments, analyze volumetric imaging datasets
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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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associate will be conducting research on topics in machine learning and computational materials science.. In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is
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Difallah in the Division of Science, New York University Abu Dhabi, seeks a Post-Doctoral Associate or a Associate Research Scientist to join a lab focused on applied machine learning. The successful
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Researcher will work in Professor Benjamin Peherstorfer’s group (https://cims.nyu.edu/~pehersto/ ) on scientific machine learning at the Courant Institute of Mathematical Sciences where they will help
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). Experience with human-factors instrumentation and data streams: eye tracking, physiological sensors, and motion capture. Familiarity with data/video coding tools and computer vision (e.g., OpenCV, scikit-learn
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concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical
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network inference and modeling, machine learning and deep learning. Experience in working with Arabidopsis and plant genome data is a strong plus. The position is expected to continue for multiple years