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and engineers. Key Responsibilities 1. AI Model Development & Testing Assist in developing machine learning and deep learning models for medical imaging analysis. Implement and fine-tune models using
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goals and those of faculty mentor; and publication of research findings/scholarship during postdoc appointment period. Projects in the Rocha lab address the evolutionary history of populations and species
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postdoc with interests in RNA virology and host-pathogen interactions. For detailed information about the laboratory’s research, see our website (http://www.mouncelab.com). Experience in molecular virology
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The Franciszek Górski Institute of Plant Physiology Polish Academy of Sciences | Poland | about 1 month ago
qualifications Experience in one or more of the following areas will be considered an advantage: RNAseq analysis pipelines, systems biology, modelling biological processes, or machine learning approaches, redox
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. The focus of this position is developing methods to disentangle dynamic, multiscale ecological signals from large, noisy observational data. This work lies at the interface of statistics, machine learning/AI
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, 10 lecturers, 20 postdocs, and 60 doctoral students. Our department has a welcoming culture which nurtures innovativeness and communication among our international and diverse faculty. The department
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, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at https://hr.duke.edu/benefits/ Duke is an Equal Opportunity Employer committed
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models that provide evidence-based reasoning for mission-critical decisions. Explainable AI for mission-critical decision support: design interpretable machine learning architectures capable of offering
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. MATLAB, C/C++, Python. Highly motivated and keen on working in an international and interdisciplinary team. Applicants with strong background in the following fields are preferred: Machine Learning Formal
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increments; excursion theory of Markov processes; Tsirelson's theory of stochastic noises; deep/machine learning; Stein's method and the central limit theorem; copulas; actuarial mathematics). Where to apply E