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fungal networks. The project is funded by a joint NIH/NSF program at the interface of mathematical and biological sciences. Job description: Lead the design, conduct, and analysis of laboratory experiments
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& Decision Neuroscience Lab (https://www.konovalab.com/ ) led by Dr. Anna Konova and located at the Rutgers Center for Advanced Human Brain Imaging Research (CAHBIR). The ADN Lab conducts decision neuroscience
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. The position involves data analysis, model development, use of AI/ML tools for both understanding the mechanisms governing long-term performance of polymers and composites and translating findings into practical
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
in which individuals are enrolled into prospective observational or intervention studies that seek to better understand and prevent posttraumatic neuropsychiatric sequelae (https://www.med.unc.edu/itr
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linear models, network analysis, etc.) experience with culturing microorganisms (fungi and/or bacteria) experience with R and/or other programming languages familiarity with bioinformatics and modeling
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studies using qualitative, quantitative, and mixed-methods approaches, including surveys, interviews, observations, social network analysis, and analysis of digital trace data. Collaborating with industry
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Postdoc Position for Computational Genomics, AI Precision Oncology, Cancer Biology and Immunobiology
University of Pittsburgh, Pittsburgh , Pennsylvania, US | Pittsburgh, Pennsylvania | United States | about 2 months agoinsights through iterative, hypothesis-driven computational analysis. 2) Characterizing the landscape of structural mutations—including intragenic rearrangements (IGRs)—across cancer types and modeling
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basis of cognition across multiple levels of analysis. The successful candidate (m,f,x) will join a vibrant and collaborative team with access to excellent infrastructure, including the university’s new
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socio-hydrosystems, from stormwater networks and surface waters to wastewater treatment plants and receiving environments. The project relies on innovative high-resolution mass spectrometry (HRMS)-based
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diverse set of time-dependent forecasting models (e.g., neural network, mechanistic, statistical, and data-driven) to serve as experts within the integrative architecture. (iii) Mixture-of-experts