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genome-resolved multi-Omics methods, statistical/metabolic modeling, and machine learning. The postdoc will apply these approaches to generate a systems-level understanding of microbiomes including
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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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, statistics, or mathematics OR a strong background in gene engineering and functional interrogation of hematopoietic stem and progenitor cells. Strong knowledge in bioinformatics, machine learning, statistics
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to effectively teach genetics, biochemistry, and molecular biology to undergraduates in the lab setting. The research projects cover a large span of life science topics and technical approaches, including genetics
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Science, Computer Science, Data Science, Neuroscience, or a related field by the start date. Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning
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-guided machine learning. You are quick to assimilate information and capable of independent research. Experience in the pharmaceutical sector is an advantage You speak and write English fluently. You are
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, solvent-based recycling process for complex plastic waste streams such as multilayer packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process
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Appointment Term: Initially 1 year, renewable Appointment Start Date: Fall 2025 but flexible Group or Departmental Website: https://www.liwanglab.org/ (link is external) How to Submit Application Materials
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areas: -developmental biology -experimental and/or theoretical biophysics -experimental and/or computational genomics -computer science, statistics, and/or machine learning with applications relevant
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physical environments. This position focuses on research at the intersection of computer graphics, generative AI, and robotics, encompassing topics such as generative modeling, reinforcement learning, multi