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principals to problem solve work. ● Ability to maintain detailed records of experiments and outcomes. ● Ability to quickly learn and master computer programs, databases, and scientific applications
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and other machine learning models (especially neural network models, time-series models) and coding in python and R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings at conferences and
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not required as part of this position. Required Qualifications: Strong mathematical background, including expertise in one or more of the following areas: machine learning, statistics, and algorithms
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, mathematics, physics, or a related field. The ideal candidate should demonstrate a record of publications in the area. Strong knowledge in machine learning, statistics and programming skills (R, Python
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resulting from T regulatory (Treg) cells by conducting genetic screens to overcome this suppression and to enhance CAR T cells for lymphoma. On the other hand, we also seek to apply the lessons learned from
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expression in single cells within their spatial context in pathomic samples. This research opportunity will be focused primarily on the development and application new image processing and machine learning
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-developing a hybrid machine learning/process-based model of anaerobic digestion processes Performing techno-economic and lifecycle analysis of microgrids build around novel biogas-fueled generation
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research programs. Required Qualifications: o Highly motivated postdoctoral researcher with: • Experience in relational databases, big data curation and analysis • Expertise in machine learning, including
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the use of R and/or Python Basic understanding of statistical modeling, and machine learning Understanding of high-throughput sequencing techniques including whole genome, whole exome, targeted capture, RNA