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that connect single-cell and spatial transcriptomic data to mechanistic, biophysically grounded models of gene regulation. There is also scope to work on exact and approximate solutions of stochastic models
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biology, neuroscience, metabolism, stem cell biology, neurodegenerative disease, cancer research, or animal models. How to Apply Please apply through the Nature Careers website or email a cover letter, CV
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administration. The work relies heavily on the use of animal models for MS and mammalian cell culture. The ideal candidate is expected to be highly motivated with a strong work ethic and demonstrated creativity
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-source modeling and collaborative research. The successful applicant will play a central role in developing and applying Tools for Energy Model Optimization and Analysis (Temoa), a widely used open-source
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University of California San Diego - Ganesan Lab | Mision de San Diego de Alcala, Baja California | Mexico | 2 months ago
. Research focus To investigate molecular and cellular mechanisms of anti-tumor immunity and test novel immunotherapy targets using cutting-edge genomic and immunological tools and mouse models. Requirements
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of computational scientists, applied mathematicians, and computer scientists to link models and algorithms with high-performance computing. Author peer reviewed papers for internal and external release as
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. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred skills: Microwave circuit design, terahertz optics, and their characterization. Knowledge about near
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or other related fields; and be skilled in cell culture, microfluidic fabrication, modeling organ systems, characterization assays such as PCR, immunostaining, flow cytometry, ELISA etc. PREFERRED
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modelling, data analysis and interdisciplinary approaches, our work investigates pathways to improve the resilience, efficiency and long-term sustainability of solar energy deployment. In this role, you will
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and machine-learning methods for rapid surrogate modeling, model calibration, state estimation, uncertainty quantification, and physics-informed prediction. Contribute to U.S. Department of Energy