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Field
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addresses the design of wholesale, balancing, reserve, and capacity markets under high shares of variable renewable generation; price formation, scarcity pricing, and locational signals; network charging and
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. This position is designed for scientists with strong computational and quantitative training who are interested in agent-based modeling, network science, infectious disease dynamics, uncertainty quantification
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support (including a Parenting and Carers Fund and the Carer’s Career Development Fund ), training, and a variety of diversity and inclusion networks. Staff can apply for flexible working to help them
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concerns applied science for and often with public and private partners. Job requirements We are looking for a highly motivated researcher with: A PhD in a relevant discipline, such as urbanism
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following criteria: A PhD or equivalent degree, already obtained, in a related field e.g., philosophy, law, computer science, social sciences, public policy, or a relevant interdisciplinary area. Interest in
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network methods. The posts will focus on classical benchmarking, including Pauli propagation, tensor networks and related numerical methods for simulating smaller systems and comparing them with quantum
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academic teaching and academic self-governance. The postdoctoral scholar will receive mentorship from the PI and the PI's network in research, grant writing, manuscript preparation, research methodology, etc
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PhD in genomics, population genetics, evolutionary genetics, forest genetics, bioinformatics or a related field; a strong background in plant, forest, population or evolutionary genetics/genomics, with
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testable computational study, communicate openly about negative as well as positive results, and work effectively with collaborators who use different scientific languages. You hold a PhD in bioinformatics
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Yale School of Medicine - Department of Genetics | New Haven, Connecticut | United States | about 2 months ago
. The position is supported by NIH funding and sits within a rich collaborative network at Yale, including the Yale Cancer Center, the Yale Stem Cell Center, the Wu Tsai Institute, and computational collaborators