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Field
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equation—rests on a physical basis that is naturally suited to the modeling of transport phenomena at the microscale, while relying on a conceptually simple algorithm with direct implementation and high
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Learn, OpenCV, PyTorch), R, SQL, HTML/CSS, C, STATA Coursework in Machine Learning, Algorithms/Advanced Data Structures, Data Science, Probability, Data Graphics and Visualizations, Modern Regression
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of the candidate and the needs of the research center. More specifically, the postdoc will work on the following topics, in collaboration with the rest of the team: Develop and apply evolutionary algorithms
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 10 days ago
artificial intelligence applications in drug development. You will gain experience researching advanced in silico prediction algorithms, analyzing machine learning approaches for toxicity pattern recognition
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of the research group. Key Responsibilities: Conduct research in CV/ML/robotics for infrastructure monitoring and automation. Develop algorithms and/or systems for sensing, perception, and robotic applications
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university. Lab maintenance, including equipment maintenance and ordering of supplies may be required depending on area and specialty. Working on the development of planning algorithms for bimanual
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, group theory, and/or graph theory will be necessary. Experience in modelling biological processes, and in algorithm development or computation will also be valuable. Proven commitment to proactively
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perform 3D single-particle tracking and establish pipelines to characterise the particle motion using a combination of established tracking algorithms and machine-learning-based approaches. Additionally
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learner, analytical thinker, creative, "hands-on", team-player. ? Experience with computational analysis, algorithm development and statistics. ? Proficiency in at least one modern programming language
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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide