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decisions focusing mainly on interpretable machine learning and its applications. The candidate must be an expert in music generation and Schenkerian analysis. The candidate will be responsible for working
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; (ii) an impact evaluation of a large-scale tree-growing program in Kenya, Tanzania, Uganda, and India; and (iii) an analysis of financial incentives for smallholder tree growing in Ethiopia. In
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Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and
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Qualifications: A PhD degree in a field related to exposure science, environmental health, or environmental chemistry; experienced in HPLC-MS analysis and other web lab skills; with publications showing analysis
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. Preferred Qualifications: Background in live imaging and image analysis in tissue or stem cell cultures. This position is onsite. The work is performed on-site or at a designated assignment location. Be Bold
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mapping the critical gene and cellular networks by which the Xist lncRNA ribonucleoprotein particles (RNPs) promote autoimmune diseases (see Dou et al., Cell 2024 , for more background). This work will
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-funded Duke lab hub for the Human Health Exposure Analysis Resource ) program, the Newborn Epigenetics STudy (NEST) longitudinal birth cohort, the Children’s Health and Discovery Initiative (CHDI
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chemoproteomics, chemical biology, and related areas. The interested candidate will work directly with experimental scientists within a wet lab setting to facilitate the management, analysis, and visualization
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analysis using appropriate machine learning techniques and contribute to the writing of technical papers and research proposals. Duke is an Equal Opportunity Employer committed to providing employment
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approaches to understand the interconnections between nutrition, health, food systems, and society. Our lab has pioneered genomics techniques that objectively track dietary intake across hundreds of plant and