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disparities, advancing interdisciplinary research and practice for sustainable and equitable economic models, and emphasizing policy’s role in mitigating adverse outcomes. With a PhD in a relevant discipline
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learning and advanced statistical modeling * Proficient programming skills in Python and/or R, experience with machine learning and omics analysis libraries (e.g., scikit-learn, TensorFlow/PyTorch
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development, patents, and publications. The successful applicant will have an opportunity to develop their leadership skills on projects related to advancing natural plant-derived compounds and/or repurposing
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connectivity of the broader community, training, networking, as well as state-of-the-art research. This post will develop artificial intelligence methods for the prediction of crystal structure, the critical
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quasi-experimental methods to identify causal effects and test the predictions of economic and sociological models. Examples of current research projects include: long-term impacts of neighborhoods and
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spans all areas of chemistry such as analytical chemistry, physical chemistry, materials chemistry, inorganic and structural chemistry and organic chemistry. The research projects are many from theory
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models
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connectivity of the broader community, training, networking, as well as state-of-the-art research. This post will develop artificial intelligence methods for the prediction of crystal structure, the critical
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(CRISPR screens, Chromatin IP, ATAC-seq) and cellular biology (cell death mechanisms, immunology), and experience with animal models and organoid cultures. Position 3 will focus on Bioinformatics