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non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory grammar. Responsibilities
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formulation, molecular-level characterization, and machine learning to develop predictive models linking chemical descriptors to adhesive properties. The work includes the development of a structured
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postdoctoral researcher will conduct cutting-edge research in areas such as cyber-physical systems security, protection of critical infrastructure, and adversarial machine learning. The position will
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Manufacturing and Machine Industry theme of the Aalto House of AI , led by Professor Ville Kyrki. The theme brings together robotics, machine learning, and electrical and mechanical engineering to work on
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expected to have: A doctorate in a Machine-Learning related field A deep knowledge of Control Theory, both classical and deep learning based A solid publication record in top level ML venues such as
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Your Job Develop machine-learning–based workflows and scientific software for segmentation, species classification, and lineage tracking in multi-species time-lapse microscopy data Optimize models
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quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational methods to study multiscale
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Your Job This position sits at the interface between electron microscopy and machine learning. We are looking for a microscopist or physicist with substantial computational practice who wants to
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Postdoctoral Researcher - Machine Learning for Plant Regulatory Genomics Plants adapt to their environment through genetic variation, but linking that variation to its ecological role across species
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geometry, number theory, data. * Qin Li: Scientific computing, machine learning, inverse problems. * Hanbaek Lyu: Combinatorics, probability, optimization, and machine learning. * Laurentiu Maxim