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and deep learning methods for large-scale genomic, clinical, and imaging biobank data, with stable multi-year NIH support. The Zhi Laboratory has a sustained track record of methods development
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have knowledge of software development principles, and machine learning, including deep learning experience, as well as a strong background in research processes, including report writing, and producing
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(payable 14 times per year) Responsibilities The applicant is expected to establish an own research group with focus on advanced machine learning and deep learning techniques for remote sensing applications
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, linear mixed models, or deep learning architectures). A solid theoretical background in literacy development, child language acquisition, or psycholinguistics. A record of academic publishing and high
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, computer vision, robotics, biomedical engineering, computer science, biomechanics, neuroscience, signal processing, or a closely related discipline. Strong expertise in machine learning and deep learning
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Equation, Stochastic simulation algorithms, and approximation methods. ● Experience with single-cell or spatial transcriptomic data analysis. ● Familiarity with machine learning and deep learning
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earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc. Documented experience in machine learning, in particular deep generative
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, Chemistry, Physics, Applied Mathematics, Materials Science, Chemical Engineering, or a related technical field. Demonstrated research experience in machine learning or deep learning for scientific
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Do you want to combine high-throughput directed evolution with machine-learning analysis of deep sequencing data to engineer better antibodies? The Sormanni Lab in the Department of Chemical
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a sequential decision-making process explored through computational simulation and deep multi-objective reinforcement learning. The project will investigate a simulation platform that reproduces