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Field
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approaches. Topics include algorithms for genomic data analysis, machine learning applications, and computational modeling of biological systems. Students will gain hands-on experience with commonly used
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of probability, statistics and optimization. * Proven expertise in the implementation and testing of algorithms. * Strong programming skills in R or Python. * Familiarity with data science and visualization
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Qualifications - Experience in developing algorithms for analysis of biological data. - Experience with single cell and spatial transcriptome data analysis. - Experience in supervised and unsupervised machine
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
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(intracranial and scalp EEG) and MRI data sets. Develop and implement algorithms for data processing and interpretation. Collaborate with clinicians and researchers to design studies and analyze results. Present
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navigation, and follow-up algorithms. Successful candidates will be required to self-disclose any misconduct history or pending research misconduct investigation including but not limited to sexual misconduct
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& Bioinformatics Shared Resources (BBSR). Will provide support on bioinformatics, analysis, model development and validation, and machine learning algorithms. Will contribute to all phases of research, including
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analyses, and data visualization. Application of latest developments and algorithms from computer vision and machine learning to spatial data analyses in geosciences. Experience working with satellite
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(providing detailed information about each work to be read by algorithms). 3. Manage relationships with authors, agents, buyers, and reviewers. Carry out permissions research and royalty work (coordinating
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of computer science are invited, while candidates with core expertise in robotics AI (including drones and humanoids), digital twins, software engineering, theory/algorithms, and cybersecurity are particularly