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approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory grammar
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experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory
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, design and analysis of virus-derived RNA libraries, and development of machine learning models for detecting functional elements in viral metagenomic datasets. This project is a collaboration with the
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Correction Circuits Design of parametric processes and quantum control of driven non-linear quantum devices Quantum computer architecture, hardware- and noise-aware compilers Computation with Dynamic Circuits
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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and
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platforms a plus Experience applying machine learning, artificial intelligence, and large language models to research a plus The anticipated start date is September 1, 2026. The postdoctoral position incoming
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at least one of these areas and a willingness to learn the other. Our philosophy is to chase scientific questions using the best methodology available, which usually means employing both “wetlab” and
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history, with often significant events such as exhibitions or conservation processes being kept in different systems, or by different organizations. The research topic to be explored is the extent to which
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data according to research specifications. Uses a computer terminal to input and retrieve data and to generate reports Processes and summarizes data using scientific or statistical techniques. Assists in
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approach to public health research. Candidates with research experience working with people who use drugs and community organizations that serve this population are preferred. Having a car to drive to sites