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Field
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contribute to research and model development to enhance the resilience of domestic and global supply chains for clean energy technologies. Lead technical and policy analysis to inform decision-makers
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crop improvement. The successful candidate will work on chromosome-scale genome assembly, gene annotation, structural variation discovery and development of genomics tools to accelerate breeding across
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, senescence, and wound repair; collects and analyzes data for research sponsored by appropriate agencies and Institutions; identifies and selects problems to be studied; develops and troubleshoots new
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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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of applying a wide variety of scientific principles and theories. Maintains substantial knowledge of state-of-the-art principles and theories. Develops advanced analytical models and systems and provides
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studies, functioning as a subject expert on one of more phases of the project(s); prepare and/or present seminars, talks or lectures for dissemination of knowledge, particularly the results of research
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in the Department of Molecular, Cellular & Biomedical Sciences at the University of New Hampshire. The lab’s research centers on development and application of mass spectrometry-based proteomics and
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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/maintenance, the collective supervision of graduate and undergraduate students, and dedicated activities related to professional development. Responsibilities: Research: Conduct advanced research in
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Postdoctoral Associate to join a multidisciplinary research team focused on developing energy-efficient and fault-tolerant AI systems that can operate reliably in the radiation-rich environment of space. The