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of mouse behavioral paradigms is required. Extensive computer programming experience in python or Matlab and the ability to deal with large, complex datasets are required. Experience with preparation and
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the
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, including but not limited to cancer, metabolic disorders, and infections. The research design involves the integration of large-scale biological datasets derived from both the host and the microbiome
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-derived organoid models. You will work closely with in-house technology platforms, including the Single Cell Genomics Facility, Big Data Core and High Throughput Screening Facility. Our research is embedded
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for one year. The associate will have the opportunity to assist with data analysis and manuscript writing for a recently completed large randomized clinical trial on smoking cessation induction within a
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linear, mixed-integer, and stochastic programming. Work with programming languages such as Python, Julia, or C++ to build robust analytical tools and perform large-scale data analysis. Collaborate with
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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The successful candidate will be responsible for developing computational and systems biology approaches to analyze spatial omics data and single-cell omics data (e.g., scRNA-seq, scATAC-seq, single
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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project sites. The research will help gauge views and perceptions of hosting landowners, agricultural and rural community members, developers, and policymakers through qualitative and quantitative data